*jѥvddlmZddlmZddlZddlmZmZmZm Z m Z ddl Z ddl Z ddlmZmZddlmZmZddlmZddlmZdd lmZmZdd lmZdd lm Z dd l!m"Z"dd l#m$Z$ddl%m&Z&m'Z'm(Z(ddl)m*Z*m+Z+m,Z,m-Z-m.Z.m/Z/ddl0mZm1Z1m2Z2m3Z3ddl4m5Z5ddl6m7Z7ddl8m9Z9ddl:m;Z;mZ>m?Z?ddl@mAZAddlBmCZCddlDmEZEddlFmGZGddlHmIZIer ddlJZKddlLmMZNer&ddlOmPZPddlJZJddlQmRZRmSZSmTZTmUZUmVZVmWZWmXZXmYZYmZZZddl[m\Z\e"de(Gdd e'Z]Gd!d"e9Z^e"d#Gd$d%e^eAZ_y)&) annotations)partialN) TYPE_CHECKINGAnyLiteralSelfcast) get_optionusing_string_dtype)libmissing) NDArrayBacked)ensure_string_array) HAS_PYARROWPYARROW_MIN_VERSION)function)Pandas4Warning) set_module)find_stack_level)ExtensionDtypeStorageExtensionDtyperegister_extension_dtype) is_array_like is_bool_dtypeis_integer_dtypeis_object_dtypeis_string_dtype pandas_dtype)r nanopsops roperator)isin)masked_reductions)ExtensionArray) FloatingArray FloatingDtype) IntegerArray IntegerDtype)NumpyExtensionArray) extract_array)check_array_indexer)isna)printing)MutableMapping) ArrayLikeAxisIntDtypeDtypeObj NumpySorterNumpyValueArrayLikeScalarnpttype_t)SeriespandasceZdZdZeddZeddZeddZdZde jf ddZ ddZ dd Z dd Zdfd Zd Zedd ZeddZddZddZ ddZxZS) StringDtypea Extension dtype for string data. .. warning:: StringDtype is considered experimental. The implementation and parts of the API may change without warning. Parameters ---------- storage : {"python", "pyarrow"}, optional If not given, the value of ``pd.options.mode.string_storage``. na_value : {np.nan, pd.NA}, default pd.NA Whether the dtype follows NaN or NA missing value semantics. Attributes ---------- storage na_value Methods ------- None See Also -------- BooleanDtype : Extension dtype for boolean data. Examples -------- >>> pd.StringDtype() )> >>> pd.StringDtype(storage="python") )> c>|jtjuryy)Nstringstr) _na_value libmissingNAselfs >Z]] *c|jS)ac The missing value representation for this dtype. This value indicates which missing value semantics are used by this dtype. Returns ``np.nan`` for the default string dtype with NumPy semantics, and ``pd.NA`` for the opt-in string dtype with pandas NA semantics. See Also -------- isna : Detect missing values. NA : Missing value indicator for nullable dtypes. Examples -------- >>> ser = pd.Series(["a", "b"]) >>> ser.dtype >>> ser.dtype.na_value nan )r?rBs rDna_valuezStringDtype.na_values,~~rFc|jS)a| The storage backend for this dtype. Can be either "pyarrow" or "python". See Also -------- StringDtype.na_value : The missing value for this dtype. Examples -------- >>> ser = pd.Series(["a", "b"]) >>> ser.dtype >>> ser.dtype.storage 'pyarrow' )_storagerBs rDstoragezStringDtype.storages&}}rFrKr?Nc|td}|dk(r trd}nd}|dvrtd|d|dk(rtstdtd t |t r&tj|rtj}n |tjurtd |tt||_||_y) Nzmode.string_storageautopyarrowpython>rPrOz+Storage must be 'python' or 'pyarrow'. Got z instead.z pyarrow>=z, is required for PyArrow backed StringArray.z('na_value' must be np.nan or pd.NA, got )r r ValueError ImportErrorr isinstancefloatnpisnannanr@rAr r>rJr?)rCrKrHs rD__init__zStringDtype.__init__s ? !67G& 'G&G / /=gYiP  i  /01&&  h &288H+=vvH Z]] *GzRS SS'* !rFcN|jdk(rdnd}d|d|jdS)NrOzstorage='python', z rL)rCrKs rD__repr__zStringDtype.__repr__s/ 1"7Kwiy0@CCrFc,t|tr'|dk(s||jk(ry |j|}t|t |r3|j|jk(xr|j|juSy#tt f$rYywxYw)Nr=TF) rSr>rEconstruct_from_string TypeErrorrRtyperKrH)rCothers rD__eq__zStringDtype.__eq__s eS ! ETYY$6 2259 eT$Z (<<5==0TT]]enn5T T {+  sBBBc||jdd|_|jdtj|_y)NrKrPr?)poprJr@rAr?)rCstates rD __setstate__zStringDtype.__setstate__s* )X6 ; >rFc t|SN)super__hash__)rC __class__s rDrizStringDtype.__hash__sw!!rFc>t|j|jffSrg)r;rKrHrBs rD __reduce__zStringDtype.__reduce__sT\\4==999rFctSrg)r>rBs rDr_zStringDtype.types rFc$t|tstdt||dk(r|S|dk(r!t r|t j S|dk(r |dS|dk(r |d Std |jd |d ) a| Construct a StringDtype from a string. Parameters ---------- string : str The type of the name. The storage type will be taking from `string`. Valid options and their storage types are ========================== ============================================== string result storage ========================== ============================================== ``'string'`` pd.options.mode.string_storage, default python ``'string[python]'`` python ``'string[pyarrow]'`` pyarrow ========================== ============================================== Returns ------- StringDtype Raise ----- TypeError If the string is not a valid option. z.'construct_from_string' expects a string, got r=r>rHzstring[python]rPrKzstring[pyarrow]rOzCannot construct a 'z' from '')rSr>r^r_r rUrW__name__)clsr=s rDr]z!StringDtype.construct_from_string s8&#&@fO  X 5L u_!3!5' ' ' 'x( ( ( (y) )23<<.PQRS SrFcddlm}|jdk(r"|jtj urt S|jdk(r|jtj ur|S|jdk(rt S|S)zq Return the array type associated with this dtype. Returns ------- type r)ArrowStringArrayrPrO)pandas.core.arrays.string_arrowrurKr?r@rA StringArray)rCrus rDconstruct_array_typez StringDtype.construct_array_type7sc  <<8 #*--(G  \\Y &4>>Z]]+J# # \\X % # #rFct}t}|D]s}t|tr7|j|j|j|j Jt|t jr|jdvrsyt|dk(rd}ntt|}t|dk(rtj}ntt|}t||S)N)UTrOrKrH)setrSr;addrKrHrUdtypekindlennextiterr@rA)rCdtypesstorages na_valuesrrKrHs rD_get_common_dtypezStringDtype._get_common_dtypeLs5E E%- U]]+ enn-E288,z1I x=A G4>*G y>Q !}}HDO,H7X>>rFc|jdk(rjddlm}m}|tj j |js(tj|t j}|||Sddl }t||jr|g}n |j}g}|D]<}|jd}t!||j"}|j%|>t'|dk(rt)j*gt,}nt)j.|}t0j3t0}t5j6||||S) zH Construct StringArray from pyarrow Array/ChunkedArray. rOr)ru_check_pyarrow_availablerNF)zero_copy_onlyro)rKrvrurpatypesis_large_stringr_pcr large_stringrOrSArraychunksto_numpyrrHappendrrUarrayobject concatenaterw__new__rrX) rCrrurrOrresultsarrnew_string_arrays rD__from_arrow__zStringDtype.__from_arrow__hs <<9 $  % &88++EJJ7r'89#E6 6 %/Gll%l8)# Fs#  v;! ((2V,C..)C'..{;/d;rF)returnr>)rlibmissing.NAType | float)rKz str | NonerHrrNone)r`rrbool)rdzMutableMapping[str, Any]rr)rint)rz type[str])rr)rztype_t[BaseStringArray])rzlist[DtypeObj]rzDtypeObj | None)rz$pyarrow.Array | pyarrow.ChunkedArrayrBaseStringArray)rr __module__ __qualname____doc__propertyrErHrK _metadatar@rArXr[rarerirlr_ classmethodr]rxrr __classcell__rjs@rDr;r;ds#J.()I#.8mm!"!",!"  !"FD"? ":(T(TT$*?8, 9, , rFr;ceZdZUdZded<dZd dZdddZejddf dd Z dd Z ejdf dd Z ddfd Z xZS)rz8 Mixin class for StringArray, ArrowStringArray. r;rc|tjtjtjfvrt |t j r|jtk(ro|jddjd}tjd|d|jdtt|||jtSt S)N_rqz'' operations between boolean dtype and z| are deprecated and will raise in a future version. Explicitly cast the strings to a boolean dtype before operating instead.) stacklevel)r!ror_rand_rxorrSrUndarrayrrrrstripwarningswarnrrastypeNotImplemented)rCr`opop_names rD_logical_methodzBaseStringArray._logical_methods 9>>9??INNC C5"**- t#kk!"o++C0G MMG9CDJJ<PPP+-  eT[[./ /rFc|jdkDr|Dcgc]}|jc}St|jScc}w)a Return a list of the value. These are each a scalar type, which is a Python scalar (for str, int, float) or pandas scalar (for Timestamp/Timedelta/Interval/Period) Returns ---------- list Examples ---------- >>> arr = pd.array(["a", "b", "c"]) >>> arr.tolist() ['a', 'b', 'c'] r)ndimtolistlistr)rCxs rDrzBaseStringArray.tolists@$ 99q=(,-1AHHJ- -DMMO$$.sAc@ttjd| }|S)N)   ) escape_chars quote_strings)rr- pprint_thing)rCboxed formatters rD _formatterzBaseStringArray._formatters%  ! !+#) rFNTc |jjtjur|j |||Sddlm}| |j}|tjur|jj}t|}tj|}t|s t|rt|rt}n|}t|} | rd}n#|tjdk(r t|}tj|||j!dd|tjt#t$|} | sd|dd|| |S|j'|||||S) N)rHrr) BooleanArrayrruint8FconvertrHr)rrHrUrW_str_map_nan_semantics pandas.arraysrr no_defaultr,asarrayrrr'rmap_infer_maskviewr r__str_map_str_or_object) rCfrHrrrmaskr constructorna_value_is_naresults rD_str_mapzBaseStringArray._str_maps4 ::  "&& (..q85.Q Q. =JJE s~~ %zz**HDzjj E "mE&:&* * !(^N"((6**>'' '"!hhtD%01 F"Qvt, ,..uhQM MrFct|rt|stj|||j dd|}|j j dk(r:ddl}|j|||jd}|j|St|||j Stj|||j dS) NrF)rrHrOrT)rr_ from_pandasr) rrr rrrrKrOrr_from_pyarrow_arrayr_)rCrrHrrrrrs rDrz&BaseStringArray._str_map_str_or_objects 5 !/%*@''Q '*EHFzz!!Y.$"OBOO,=4//77"tDz& ;;%%c1dii.@A ArFc v| |j}|tjur$t|rd}n|jj}t |}t j|}t|s t|rt |}|rt|rd}nd}tj|||jdd|t jtt|}|r?t|r4|jr$|jd}t j||<|S|j!|||||S)NFrrrfloat64)rr rrrHr,rUrrrrr r_anyrrWr)rCrrHrrrrrs rDrz&BaseStringArray._str_map_nan_semantics-s  =JJE s~~ %U# ::..Dzjj E "mE&:!(^N#E* H %H'' '"!hhtD%01 F"25"9dhhj y1!vvt M..uhQM MrFc:| tdt| S)Nz)Cannot change data-type for string array.)r^rhr)rCrrjs rDrzBaseStringArray.viewYs!  GH Hw|~rF)rrF)rr)r Dtype | Nonerr)rz np.ndarrayrnpt.NDArray[np.bool_])rrrg)rrrr)rrrrr__annotations__rrrr rrrrrrrs@rDrrs $%," 3N 3N  3Nj&B &B $ &BR..*N1=*NXrFrz pandas.arraysceZdZdZdZddd d&fdZd'dZdZeddd d(d Z edd  d)d Z d*fd Z ed+d Z d,dZ d-dZdZd.fd Zd/dZd0dZd1dZd2d3fd Zdddd d4dZddd5dZd6fd Zd7d8dZd7d8dZdddd d9d Zd2d:fd! Zd;dfd# Zd$ZeZd?d%Z xZ!S)@rwar Extension array for string data. .. warning:: StringArray is considered experimental. The implementation and parts of the API may change without warning. Parameters ---------- values : array-like The array of data. .. warning:: Currently, this expects an object-dtype ndarray where the elements are Python strings or nan-likes (``None``, ``np.nan``, ``NA``). This may change without warning in the future. Use :meth:`pandas.array` with ``dtype="string"`` for a stable way of creating a `StringArray` from any sequence. StringArray accepts array-likes containing nan-likes(``None``, ``np.nan``) for the ``values`` parameter in addition to strings and :attr:`pandas.NA` dtype : StringDtype Dtype for the array. copy : bool, default False Whether to copy the array of data. Attributes ---------- None Methods ------- None See Also -------- :func:`array` The recommended function for creating a StringArray. Series.str The string methods are available on Series backed by a StringArray. Notes ----- StringArray returns a BooleanArray for comparison methods. Examples -------- >>> pd.array(["This is", "some text", None, "data."], dtype="string") ['This is', 'some text', , 'data.'] Length: 4, dtype: string Unlike arrays instantiated with ``dtype="object"``, ``StringArray`` will convert the values to strings. >>> pd.array(["1", 1], dtype="object") ['1', 1] Length: 2, dtype: object >>> pd.array(["1", 1], dtype="string") ['1', '1'] Length: 2, dtype: string However, instantiating StringArrays directly with non-strings will raise an error. For comparison methods, `StringArray` returns a :class:`pandas.BooleanArray`: >>> pd.array(["a", None, "c"], dtype="string[python]") == "a" [True, , False] Length: 3, dtype: boolean extensionNFrcopyc| t}t|}t| ||t |t |s|j |tj||j|y)Nr) r;r*rhrXrSr_ _validater_ndarray)rCvaluesrrrjs rDrXzStringArray.__init__sb =MEv& d+&$t*- NN5 !  MM  rFc|jtjurt|jr,t j |jds td|jjdk7r#td|jjd|jjdkDr/t j|jjdy t j|jy t|jr,t j |jds td |jjdk7r td y ) z*Validate that we only store NA or strings.Tskipnaz7StringArray requires a sequence of strings or pandas.NArz>StringArray requires a sequence of strings or pandas.NA. Got 'z' dtype instead.r|Kz1StringArray requires a sequence of strings or NaNz]StringArray requires a sequence of strings or NaN. Got '{self._ndarray.dtype}' dtype instead.N) r?r@rArrr is_string_arrayrQrrconvert_nans_to_NAravel)rCrs rDrzStringArray._validates% ??jmm +4==!#*=*= d+!M}}""h.  ++,,<> }}!!A%&&t}}':':3'?@&&t}}54==!#*=*= d+!!TUU}}""h. I/rFc t|r|jjSt|ts2t d|d|jdt |jd|S)NInvalid value ' ' for dtype '3'. Value should be a string or missing value, got ' ' instead.)r,rrHrSr>r^r_rrrCvalues rD_validate_scalarzStringArray._validate_scalarsf ;::&& &E3'!% djj\B115e1E1E0FjR  rFcn|rAt|tr|dk(s,t|}t|tr|jdk(s4Jt rtdt j}n td}ddlm }|j}t||r7|j}|j}tj||dd}|||<nBtj|rt j |}tj||| }|j#|}t%j&||||S) Nr=rPr}rpr)BaseMaskedArrayF)rconvert_na_valuer)rHr)rSr>rr;rKr rUrWpandas.core.arrays.maskedrrH_mask_datar ris_pyarrow_arrayrrrrX) rsscalarsrrrrHrrrs rD_from_sequencezStringArray._from_sequences *UC0Uh5F 'Ee[1emmx6O OO  !266BE1E=>> g / I]]F,,TE%F!)F9 ##G,((7+,,WxdSF;;s+/?rFrc*|j|||S)Nr)r )rsstringsrrs rD_from_sequence_of_stringsz%StringArray._from_sequence_of_stringss!!'T!BBrFct||}t|jtr|j |j}|Srg)rh_cast_pointwise_resultrSrr;r)rCrrrjs rDrz"StringArray._cast_pointwise_result!s7/7 fllK 0]]4::.F rFctj|t}|j|dd|||j |dS)NrFr)rUemptyrrHr)rsshaperrs rD_emptyzStringArray._empty(s<%v.NNq 6'..u5.AArFcddl}||j}|jj}d||j <|j ||S)z6 Convert myself into a pyarrow Array. rN)r_)rOr=rrr,r)rCr_rrs rD__arrow_array__zStringArray.__arrow_array__.sN  <299;D##%"tyy{rxxT**rFcJ|j}||jjfSrg)rrrH)rCrs rD_values_for_factorizez!StringArray._values_for_factorize;s mmDJJ''''rFc @tj|rgt|r|jj}|St |t s2td|d|jdt|jd|St|d}t|stj|t}n@t |jt|jr|Stj|}t|r"tj |ds td |S) z1Maybe convert value to be StringArray compatible.rrrrT) extract_numpyrrz]Invalid value for dtype 'str'. Value should be a string or missing value (or array of those).)r is_scalarr,rrHrSr>r^r_rrr*rrUrrrrrs rD_maybe_convert_setitem_valuez(StringArray._maybe_convert_setitem_value@s == E{ ++, + s+%eWM$**F::>u+:N:N9OP( "%t><= =11%8!$,]]3' }}U+ lHI I{{djj( 5)E{88:!JJLE)-)<)r,rrzerosrrr r")rCrvals rDr"zStringArray.isins fo . v~ .?6<<3P]]4::E]:F&&rzz&'9$G$*PFSjc.Bd3iSFP 6{88DJJd;;((tzz(BFBJJt$bjj&899Qs  E2ETcLt|}||jk(r|r|jS|St|trX|j j}|j }d||<|j|j}t||dSt|trN|j}|j }d||<|j|j}t||dSt|trtj|||Stj|tj rU|j j}|j }d||<|j|}tj"||<|St$|||S)NrFr0)rrrrSr(rr,r numpy_dtyper'r&r%rr$rU issubdtypefloatingrWrh)rCrrrrrarr_earjs rDrzStringArray.astypesTU# DJJ yy{"K | ,--$$&C99;DCIZZ 1 12F59 9 } -YY[F99;DF4L]]5#4#45F E: : ~ .!((ud; ; ]]5"++ .--$$&C99;DCIZZ&F66F4LMw~eT**rFr)rkeepdimsaxisc x|jjtjurK|dvrG|dk(r!t j |j |St j|j |S|dvr7t||d ||d|}|r|j|g|jS|Std|d) N)rallrr)minmaxargminargmaxsum)rr0rzCannot perform reduction 'z' with string dtype) rrHrUrWrnananyrnanallgetattrr r^)rCrErr/r0kwargsrs rD_reducezStringArray._reduces ::  "&& (T^-Cu}}}T]]6BB}}T]]6BB < <(WT4(LTLVLF**F84::*FFM4TF:MNOOrFrc |dk(rd|d|jd}t|d}d}|j}tjtj j tjj d|}|jrtdt|}tj|rt|||jS|r^|d k(rtj|d |}n|j}tj |d d tj |dd nVtj"|} tj$t'|| z d}|jj(|dd|d| }||} |tj*| |f} n-|+tj||jj(| } t|| |j} | S)a Return an ExtensionArray performing an accumulation operation. The underlying data type might change. Parameters ---------- name : str Name of the function, supported values are: - cummin - cummax - cumsum - cumprod skipna : bool, default True If True, skip NA values. **kwargs Additional keyword arguments passed to the accumulation function. Currently, there is no supported kwarg. Returns ------- array Raises ------ NotImplementedError : subclass does not define accumulations cumprodz operation 'z' not supported for dtype 'rqN)cumsumcummincummaxrrr@rZpadr)methodr0backfillr)rr^rrUr@minimum accumulatemaximum_hasnar r,r2r_whererr pad_or_backfill_inplacer6rrrHhstack) rCrErr<msgtailna_maskrnp_funcidx np_resultrs rD _accumulatezStringArray._accumulates8 9 v%@ ANCC. #'%)--iijj++jj++    ;;2DMBGvvg!tDz'<<8# hhwG%V%4 ::  *-- /]]7+F rFcz|jj}|r"|tj|jzS|Srg)rnbytesr memory_usage_of_objects)rCdeeprs rD memory_usagezStringArray.memory_usageIs3%% C77 FF F rFcP|j}t|rn|3tj|dxstj|d}n;tj||dxstj||d}nd}|r t dt ||||S)a8 Find indices where elements should be inserted to maintain order. Find the indices into a sorted array `self` (a) such that, if the corresponding elements in `value` were inserted before the indices, the order of `self` would be preserved. Assuming that `self` is sorted: ====== ================================ `side` returned index `i` satisfies ====== ================================ left ``self[i-1] < value <= self[i]`` right ``self[i-1] <= value < self[i]`` ====== ================================ Parameters ---------- value : array-like, list or scalar Value(s) to insert into `self`. side : {'left', 'right'}, optional If 'left', the index of the first suitable location found is given. If 'right', return the last such index. If there is no suitable index, return either 0 or N (where N is the length of `self`). sorter : 1-D array-like, optional Optional array of integer indices that sort array a into ascending order. They are typically the result of argsort. Returns ------- array of ints or int If value is array-like, array of insertion points. If value is scalar, a single integer. See Also -------- numpy.searchsorted : Similar method from NumPy. Examples -------- >>> arr = pd.array([1, 2, 3, 5]) >>> arr.searchsorted([4]) array([3]) rFzOsearchsorted requires array to be sorted, which is impossible with NAs present.)rsidesorter)rrr@ checknullrQrh searchsorted)rCrrmrnrhas_narjs rDrpzStringArray.searchsortedOsl-- w<~#--gaj9Z=Q=QBK>$--F1I&?))'&**=>F $ w#%d6#JJrFcddlm}m}t|trp|j j tjurJ|j j tjur$||j|j d|St||rht|trR|j j tjur&|j j tjus tStSt|tr |j}t|t|z}|}tj|r_t!|t!|k7r#t#dt!|dt!|t%|st'j(|}||}t+|dd}|j,j/dd vr6tj0|stj2|d r t5d |j,t6j8vr}t'j:|jd }|j j ||<||j||||<tj<|ds|S|j?|St'j@t!|jd }||j||||<|||} |j j t&jBurU|tDjFk(r!| jIt&jJdS| jIt&jJdS| S)Nr)ArrowExtensionArrayrFrz"Lengths of operands do not match: z != rr)mulrmulbzJCannot multiply StringArray by bools. Explicitly cast to integers instead.rrTrrro)&rrsrrSrrrHr@rArrrwrr,r is_list_likerrQrrUrr;rrris_bool is_np_dtyper^r ARITHMETIC_BINOPS empty_liker_from_backing_datar'rWoperatornerbool_) rCr`rrsrrvalid other_dtyperres_arrs rD _cmp_methodzStringArray._cmp_methods uo . ##:==8 $$ 5dkk%++Ek:EB B e0 1%1JJ'':==8 ,,JMMA))%% e[ )NNEDzDK'   E "5zSY& 8T 4E |T !' 5)%LEeWd3 ;;  S !_ 4 KK #//+s"C7  ;;#// /]]4==AF::..F4Lt}}U3U;F5M&&vd; **62 2XXc$--0?Ft}}U3U;F5M"640Gzz""bff,$"++BHHt+DD"++BHHu+EENrFc,|jfdS)Nc&|jSrg)zfill)rwidths rDz(StringArray._str_zfill..s qwwu~rF)r)rCrs `rD _str_zfillzStringArray._str_zfills}}566rF)rzStringDtype | Nonerrrr)rr;rr)rrrrrr)rrrrrr)rr/)rrwrg)rz,tuple[np.ndarray, libmissing.NAType | float])rr)rrrr)rrrr)rr/rr)T)rr)rEr>rrr/rr0AxisInt | None)rEr>rrrrw)r0rrr)NT)rrrr5)r0rrrr^rrr5)rcrrr8r)rirrr)leftN)rz$NumpyValueArrayLike | ExtensionArrayrmzLiteral['left', 'right']rnzNumpySorter | Nonerznpt.NDArray[np.intp] | np.intp)rrrr)"rrrrr_typrXrrrr r rrrrrrr"r%r"rr=rSrUr3r4r7rerjrpr _arith_methodrrrs@rDrwrw_sNb D6: 2 AE  D /3%% ,% ;?% % % N=BC .C6:C CC BB +( 8(03 8 :$+J PP P  P  P.8<Pd< 99 $ 99 9  9 9$*0%) GK3GK'GK# GK ( GKRGR M7rFrw)` __future__r functoolsrr}typingrrrrr rnumpyrUpandas._configr r pandas._libsr r r@pandas._libs.arraysrpandas._libs.libr pandas.compatrrpandas.compat.numpyrrX pandas.errorsrpandas.util._decoratorsrpandas.util._exceptionsrpandas.core.dtypes.baserrrpandas.core.dtypes.commonrrrrrr pandas.corerr r!pandas.core.algorithmsr"pandas.core.array_algosr#pandas.core.arrays.baser$pandas.core.arrays.floatingr%r&pandas.core.arrays.integerr'r(pandas.core.arrays.numpy_r)pandas.core.constructionr*pandas.core.indexersr+pandas.core.missingr,pandas.io.formatsr-rOrpyarrow.computecomputercollections.abcr.pandas._typingr/r0r1r2r3r4r5r6r7r9r8r;rrwr8rFrDrs" .0/(5  (52:24$& .    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