o Ti+@sdZddlmZddlmZddlmZmZmZmZm Z ddl m Z ddl Z ddl Z ddlmZddlmZmZdd lmZmZddlZdd lmZddlZddlZdd lmZmZddlm m!Z"dd l#m$Z$m%Z%ddl&Z'dd l&m(Z(m)Z)m*Z*m+Z+m,Z,m-Z-ddl.m/Z0ddl1m2Z2ddl3m4Z4m5Z5ddl6m7Z7erddl8m9Z9m:Z:zddl;ZYnw[ddl?Z?ze?@dWn e?jAydZ?YnwdddZBdddZCdd d!ZDejEjFgZGe7ejHe7d"kreGIejEjJejKjLd#deMeGd$ejKNd#d%OD]ZPeQe'jRjSePZTeUeTejVeTeWd&d'eXd(q d)OD]"ZPeQe'jRjSePZTeUeTejVeTeWd*d+eXejWd,d-d.d/q-d0OD]"ZPeQe'jRjSePZTeUeTejVeTeWd1d2eXejWd,d-d.d3qTejYdd4d5ZZejYdd6dd7d8Z[ejYgd9d:d;d<d=d>Z\e\Z]ejYd,d?gd@d;d<dAdBZ^ejYgdCdDdEdFZ_ejYgdCdDdGdHZ`ejYddgdDdIdJZaejYgdKdDdLdMZbejYgdNdDdOdPZcejYgdQdDdRdSZdejYgdQdDdTdUZeejYddVdWdXdYdZejfd[e"gd\d]gdDd^d_ZhejYdVdWdXdYdZejfd[e"gd\d]gdDd`daZiejYddgdDdbdcZjejYgdddDdedfZkejYdgdhgdDdidjZlejYe0jmdkd;d<dldmZnenZoejYdejpe'jqgdDdndoZrerZsejYe0jtdpd;d<dqdrZueuZvejYe(e+gdDdsdtZwejYe4e+gdudvgd<dwdxZxexZyejYe4e+e'jzggdyd<dzd{Z{ejYe4e+e(e'jzgd|d;d<d}d~Z|e|Z}ejYddZ~ejYddZejYddZejYdddZejYdddZddZddZide0dde0dde0jdddde0dde0dde0dde0jdddde0jdddde0jdddde0jdddde0jdddde0jdddde0jdddde0jdddde0jdddde0jdddde0dee4ejdddke0jdddde0jdddde0de0de4ge5egdgdeee4gde4eddde4eddde4eddde4ededde4e'jze0ddddZe>re4e'jze0dddZeed<ejYedDdduZeZejYddeDdDddZeZejYddeDdDddZejYdddZejYdddZejYdddZddÄZddńeDZejYdddDŽZejYdddɄZddńe0jDZieeeZejYedDdd̄Zddńe0jDZieeeeZejYedDddτZejYdddфZejYdddӄZejYdddՄZejYdddׄZejYdddلZejYe)dd+dڍe%ddۃfe)dddڍe%ddۃfe*ddddfe*ddddfe-ddde$dddfe,dddfgdDddZejYe0jdDddZejYe je2je je2je je2je je2je je2je je2je je2je je je je je je je je2je je2je je2jgdDddZejYe je2je je2je je2je je2je je2je je2je je2jgdDddZgdZejYedDddZddgZejYedDddZeeZejYedDddZejYe je je je je je jgdDddZejYgddDddZejYgddDddZgdZejYedDddZejYdd ZejYdd d ZejYdd dZejYdddZejYdddZddddddddddeeededede je ed,de edddd gZe?durdee?@de?@dgd!deDZe"eeejYeed<d"d#Ze"eed,dejYed,ded,dd<d$d%ZeZd&d'eee jgZe?dureIe?@dejYedDd(d)ZeZejYe0jdDd*d+ZejYdejfde"gd,d]gdDd-d.ZejYd/ejfd,e"gd,d]ejfd0e"gd,d]gdDd1d2ZejYd3ejfd,e"gd,d]gdDd4d5ZeZejYe0jdDd6d7ZejYe0jdDd8d9ZejYd:dejfde"gd,d]ejfd;e"gd,d]gdDd<d=ZejYe0jdDd>d?ZejYe0jdDd@dAZejYddCdDZejYe0jdDdEdFZejYe0jdDdGdHZejYe0jdDdIdJZejYe0jdDdKdLZejYe0j dDdMdNZ ejYe0j dDdOdPZ ejYe0j dDdQdRZejYe0jdDdSdTZejYe0jdDdUdVZejYe0je0jdDdWdXZejYe0je0je0je0jdDdYdZZejYe0jdDd[d\ZejYe0jdDd]d^ZejYe0jdDd_d`ZejYe0jdDdadbZejYe0jdDdcddZ ddeejpdfgfddee'j!dfgfdgdee'jqdfgfdhdiejpdjgfdkejpejpejpgfdkgfdldeejpdgfdgdeejpdmgfdndoejpdmgfdpd,ejpdgfdqd,ejpdmgfdre d,ejpe dgfddejpdgfdde'j!dgfdse"dtejpe"dugfde-dvejpe-dwgfdxedyd,d,ejpedzd,d,gfd{d|ejpd}gfded,ejpedgfd~ed,ejpedgfde*dye'jqe*dzgfde)dd,ejpe)ddgfgZ#ee#\Z$Z%ejYe#e$d<ddZ&ejYddZ'ejYgddDddZ(ejYdde'jSj)DdDddZ*ejYddd;gdDddZ+eYddZ,ejYdddejpejpejpfejpe'jqdfejpe'j!dfe'j!e'j!e'j!fgdDdddZ-ejYe0j.e0j/e0j0gdDddZ1ejYe0j/e0j0gdDddZ2ejYe0j.e0j0gdDddZ3ejYe0j.e0j/gdDddZ4ejYe0j5e0j/gdDddZ6ejYe0j7e0j0gdDddZ8ejYdddZ9ejYdddZ:ddgZ;e?du re;Ie?@dejYe;dDdddZThe behavior of DatetimeProperties.to_pydatetime is deprecated)z pandas.core.generic.NDFrame.boolzY(Series|DataFrame).bool is now deprecated and will be removed in future version of pandas)z!pandas.core.generic.NDFrame.firstzqfirst is deprecated and will be removed in a future version. Please create a mask and filter using `.loc` instead)zResampler.fillnaz+DatetimeIndexResampler.fillna is deprecated)DataFrameGroupBy.fillnaz3DataFrameGroupBy.fillna with 'method' is deprecated)r;z,DataFrame.fillna with 'method' is deprecatedadd_doctest_importsz/frame/) getoptionr2r3r4Z usefixturesr6ZnodeidZ arraymanager)itemsconfigZ is_doctestZignored_doctest_warningsr+r-r/r(r(r)pytest_collection_modifyitemss+  r@z6.83.2ci)deadlineZsuppress_health_checkz)MonthBegin MonthEnd BMonthBegin BMonthEndic)n normalizez%YearBegin YearEnd BYearBegin BYearEnd )Z min_valueZ max_value)rDrEmonthz1QuarterBegin QuarterEnd BQuarterBegin BQuarterEndi)rDrEZ startingMonthcCst|d<t|d<dS)z: Make `np` and `pd` names available for doctests. nppdN)rLrM)Zdoctest_namespacer(r(r)r<s r<)ZautousecCstdddS)z< Configure settings for all tests and test modules. Zchained_assignmentraiseN)rMZ set_optionr(r(r(r)configure_testssrO)rrHindexcolumnscCdt|SNzaxis=reprxr(r(r) rX)paramsidscC|jS)z@ Fixture for returning the axis numbers of a DataFrame. paramrequestr(r(r)axis rarQcCrRrSrTrVr(r(r)rXrYcCr\)zA Fixture for returning aliases of axis 1 of a DataFrame. r]r_r(r(r)axis_1rbrc)TFN)rZcCr\)a Pass in the observed keyword to groupby for [True, False] This indicates whether categoricals should return values for values which are not in the grouper [False / None], or only values which appear in the grouper [True]. [None] is supported for future compatibility if we decide to change the default (and would need to warn if this parameter is not passed). r]r_r(r(r)observed  rdcCr\)z6 Boolean 'ordered' parameter for Categorical. r]r_r(r(r)ordered-rbrfcCr\)z% Boolean 'skipna' parameter. r]r_r(r(r)skipna5rbrg)firstlastFcCr\)z[ Valid values for the 'keep' parameter used in .duplicated or .drop_duplicates r]r_r(r(r)keep=rj)bothneitherleftrightcCr\)zA Fixture for trying all interval 'inclusive' parameters. r]r_r(r(r)inclusive_endpoints_fixtureFrbrp)rnrorlrmcCr\)z< Fixture for trying all interval closed parameters. r]r_r(r(r)closedNrbrqcCr\)zS Secondary closed fixture to allow parametrizing over all pairs of closed. r]r_r(r(r) other_closedVrbrrgzipbz2zipxztarZzstdZ zstandard)ZmarkscCr\)zK Fixture for trying common compression types in compression tests. r]r_r(r(r) compression^rxcCr\)zk Fixture for trying common compression types in compression tests excluding uncompressed case. r]r_r(r(r)compression_onlypryrzcCr\)z, Fixture that an array is writable. r]r_r(r(r)writablerbr{)innerouterrnrocCr\)z: Fixture for trying all types of join operations. r]r_r(r(r) join_typerbr~nlargest nsmallestcCr\)z1 Fixture for trying all nselect methods. r]r_r(r(r)nselect_methodrbrcC t|jSNtype__name__rVr(r(r)rX cCr\)z/ Fixture for each null type in pandas. r]r_r(r(r) nulls_fixturerbrcCr\)zL Fixture for each null type in pandas, each null type exactly once. r]r_r(r(r)unique_nulls_fixturerbrcCrrrrVr(r(r)rXrcCr\)z- Fixture for each NaT type in numpy. r]r_r(r(r)np_nat_fixturerbrcCr\)z; Fixture to parametrize over DataFrame and Series. r]r_r(r(r)frame_or_seriesrbrrPseriescCr\)z Fixture to parametrize over Index and Series, made necessary by a mypy bug, giving an error: List item 0 has incompatible type "Type[Series]"; expected "Type[PandasObject]" See GH#29725 r]r_r(r(r)index_or_seriesrer)rPrarraycCr\)zG Fixture to parametrize over Index, Series, and ExtensionArray r]r_r(r(r)index_or_series_or_arrayrbrcCr\r)rrVr(r(r)rXcCr\)z] Fixture to test behavior for Index, Series, DataFrame, and pandas Array classes r]r_r(r(r)box_with_arrayrkrcCsGdddt}|S)z, Fixture for a dictionary subclass. c@seZdZdddZdS)z"dict_subclass..TestSubDictr!r"c_stj|g|Ri|dSr)dict__init__)selfargskwargsr(r(r)rsz+dict_subclass..TestSubDict.__init__Nr!r")r __module__ __qualname__rr(r(r(r) TestSubDictsr)r)rr(r(r) dict_subclasssrcCsGdddtj}|S)z8 Fixture for a non-mapping dictionary subclass. c@s2eZdZdddZddZddd Zdd d Zd S)z5non_dict_mapping_subclass..TestNonDictMappingr!r"cSs ||_dSr)_data)rZunderlying_dictr(r(r)r z>non_dict_mapping_subclass..TestNonDictMapping.__init__cSs |j|Sr)r __getitem__)rkeyr(r(r)r s zAnon_dict_mapping_subclass..TestNonDictMapping.__getitem__rcS |jSr)r__iter__rr(r(r)r rz>non_dict_mapping_subclass..TestNonDictMapping.__iter__intcSrr)r__len__rr(r(r)rrz=non_dict_mapping_subclass..TestNonDictMapping.__len__Nr)r!r)r!r)rrrrrrrr(r(r(r)TestNonDictMappings   r)rMapping)rr(r(r)non_dict_mapping_subclasss rcCs^td}|ddddddg}|jdd|jjD|_|jjgdd d |S) z DataFrame with 3 level MultiIndex (year, month, day) covering first 100 business days from 2000-01-01 with random data dcSr\r)yearrVr(r(r)rXrzAmultiindex_year_month_day_dataframe_random_data..cSr\r)rJrVr(r(r)rXrcSr\r)dayrVr(r(r)rXrcSsg|]}|dqS)i8)astype).0Zlevr(r(r) !szCmultiindex_year_month_day_dataframe_random_data..)rrJrT)Zinplace)tmZmakeTimeDataFramegroupbysumrPZ set_levelslevelsZ set_names)ZtdfZymdr(r(r)/multiindex_year_month_day_dataframe_random_datas  rrcCs*tgdgdggdgdgddgdS)z; 2-level MultiIndex, lexsorted, with string names. foobarbazquxonetwothree) rrrrHrHrrr) rrHrrrHrHrrrHrrhsecond)rcodesnames)rr(r(r(r)%lexsorted_two_level_string_multiindex&s rrcCs,|}ttjdd|tgddddS)z2DataFrame with 2 level MultiIndex with random datar) r)ABCexpr0)rPrQ)rrLrandom default_rngstandard_normalr)rrPr(r(r) multiindex_dataframe_random_data2s rcCsTtgd}tddg}tgd}tgd}ddg}t||g||g|dd S) zJ MultiIndex used to test the general functionality of this object rrr)rrrHrrr)rrHrrHrrHrhrF)rrrZverify_integrity)rrLrr)Z major_axisZ minor_axisZ major_codesZ minor_codesZ index_namesr(r(r)_create_multiindex?s  rcCs,tjddgddgtjddddggd d S) zB MultiIndex with a level that is a tzaware DatetimeIndex. rHrab20130101r US/Eastern)Zperiodstzr)r)rZ from_productrMZ date_ranger(r(r(r)_create_mi_with_dt64tz_levelSsrstringrrz datetime-tzz US/Pacific)rZperiodrrangeZint8dtypeZint16int32int64Zuint8Zuint16Zuint32Zuint64float32Zfloat64z bool-objectrr complex64 complex128)rrr)rHrr)rrrHrHrrZInt64ZUInt16ZFloat32booleanzstring[python]) bool-dtyperrZ categoricalintervalemptytuplesmi-with-dt64tz-levelmultirepeatsZ nullable_intZ nullable_uintZnullable_floatZ nullable_boolz string-pythonzstring[pyarrow]zstring-pyarrowcCst|jS)z Fixture for many "simple" kinds of indices. These indices are unlikely to cover corner cases, e.g. - no names - no NaTs/NaNs - no values near implementation bounds - ... ) indices_dictr^copyr_r(r(r)rPs cCsg|] \}}t|ts|qSr() isinstancerrrvaluer(r(r)rs rcCs|j}t|S)z8 index fixture, but excluding MultiIndex cases. )r^rr)r`rr(r(r) index_flats rcCs0g|]\}}|ds|dvst|ts|qS))rZuintfloat)rrrr) startswithrrrr(r(r)rscCst|jjdd}|j}|jdvr4|}d|ddd|d<d|ddd|d<t|Sd|d<d|d<t||S) z Fixture for indices with missing values. Integer-dtype and empty cases are excluded because they cannot hold missing values. MultiIndex is excluded because isna() is not defined for MultiIndex. Tdeep)rrrrrrHN)rr^rvaluestolistr from_tuplesr)r`indvalsr(r(r)index_with_missings    rrcCt}d|_|S)zC Fixture for Series of floats with Index of unique strings r)rZmakeStringSeriesr0sr(r(r) string_seriesrcCr)zI Fixture for Series of dtype object with Index of unique strings objects)rZmakeObjectSeriesr0rr(r(r) object_seriesrrcCr)z9 Fixture for Series of floats with DatetimeIndex ts)rZmakeTimeSeriesr0rr(r(r)datetime_seriesrrcCs*t|}tjd|}t||dddS)zHelper for the _series dictrrF)rPr0r)lenrLrrrr)rPsizedatar(r(r)_create_seriessrcCs"i|] \}}d|dt|qS)z series-with-z-indexr)rZindex_idrPr(r(r) srcCst|S)zE Fixture for tests on series with changing types of indices. rrPr(r(r)series_with_simple_indexsrcCsPgdgdg}t|}t|}tjdd}t||d}tj|j d<|S)z: Fixture with a Series with a 2-level MultiIndex. )rrrrrrrr)rrrrrrrrrrr) rurrrLrrrrnaniloc)ZarraysrrPrZserr(r(r)series_with_multilevel_indexs   r cCs$i|]}|jdtjd|dqS)-seriesr)r0r)rrZmake_rand_seriesrrr(r(r)rscCt|jjddS)z| Fixture for tests on indexes, series and series with a narrow dtype copy to avoid mutation, e.g. setting .name Tr)_index_or_series_objsr^rr_r(r(r)index_or_series_objsrcCsi|] }|jdt|qS)r )rrr r(r(r)r'scCr )z Fixture for tests on indexes, series, series with a narrow dtype and series with empty objects type copy to avoid mutation, e.g. setting .name Tr)_index_or_series_memory_objsr^rr_r(r(r)index_or_series_memory_obj4srcCsttdS)a6 Fixture for DataFrame of ints with index of unique strings Columns are ['A', 'B', 'C', 'D'] A B C D vpBeWjM651 1 0 1 0 5JyxmrP1En -1 0 0 0 qEDaoD49U2 -1 1 0 0 m66TkTfsFe 0 0 0 0 EHPaNzEUFm -1 0 -1 0 fpRJCevQhi 2 0 0 0 OlQvnmfi3Q 0 0 -2 0 ... .. .. .. .. uB1FPlz4uP 0 0 0 1 EcSe6yNzCU 0 0 -1 0 L50VudaiI8 -1 1 -2 0 y3bpw4nwIp 0 -1 0 0 H0RdLLwrCT 1 1 0 0 rY82K0vMwm 0 0 0 0 1OPIUjnkjk 2 0 0 0 [30 rows x 4 columns] r)rr getSeriesDatarr(r(r(r) int_frameAsrcC ttS)a Fixture for DataFrame of floats with DatetimeIndex Columns are ['A', 'B', 'C', 'D'] A B C D 2000-01-03 -1.122153 0.468535 0.122226 1.693711 2000-01-04 0.189378 0.486100 0.007864 -1.216052 2000-01-05 0.041401 -0.835752 -0.035279 -0.414357 2000-01-06 0.430050 0.894352 0.090719 0.036939 2000-01-07 -0.620982 -0.668211 -0.706153 1.466335 2000-01-10 -0.752633 0.328434 -0.815325 0.699674 2000-01-11 -2.236969 0.615737 -0.829076 -1.196106 ... ... ... ... ... 2000-02-03 1.642618 -0.579288 0.046005 1.385249 2000-02-04 -0.544873 -1.160962 -0.284071 -1.418351 2000-02-07 -2.656149 -0.601387 1.410148 0.444150 2000-02-08 -1.201881 -1.289040 0.772992 -1.445300 2000-02-09 1.377373 0.398619 1.008453 -0.928207 2000-02-10 0.473194 -0.636677 0.984058 0.511519 2000-02-11 -0.965556 0.408313 -1.312844 -0.381948 [30 rows x 4 columns] )rrZgetTimeSeriesDatar(r(r(r)datetime_frame^ rcCr)a Fixture for DataFrame of floats with index of unique strings Columns are ['A', 'B', 'C', 'D']. A B C D P7GACiRnxd -0.465578 -0.361863 0.886172 -0.053465 qZKh6afn8n -0.466693 -0.373773 0.266873 1.673901 tkp0r6Qble 0.148691 -0.059051 0.174817 1.598433 wP70WOCtv8 0.133045 -0.581994 -0.992240 0.261651 M2AeYQMnCz -1.207959 -0.185775 0.588206 0.563938 QEPzyGDYDo -0.381843 -0.758281 0.502575 -0.565053 r78Jwns6dn -0.653707 0.883127 0.682199 0.206159 ... ... ... ... ... IHEGx9NO0T -0.277360 0.113021 -1.018314 0.196316 lPMj8K27FA -1.313667 -0.604776 -1.305618 -0.863999 qa66YMWQa5 1.110525 0.475310 -0.747865 0.032121 yOa0ATsmcE -0.431457 0.067094 0.096567 -0.264962 65znX3uRNG 1.528446 0.160416 -0.109635 -0.032987 eCOBvKqf3e 0.235281 1.622222 0.781255 0.392871 xSucinXxuV -1.263557 0.252799 -0.552247 0.400426 [30 rows x 4 columns] )rrrr(r(r(r) float_frame{rrc Cs>tdddtjdgdddtjdgdddd tdd S) z Fixture for DataFrame of float/int/string columns with RangeIndex Columns are ['a', 'b', 'c', 'float32', 'int32']. ?rrrrrrHr)rrcrrr)rrLraranger(r(r(r)mixed_type_framesrc Cstdddtdddtdddtdddtdddtdddtdddtdddtdddtdddg }ttjdt||dS)zF Fixture for Series with a DatetimeIndex that has duplicates. irHrrrGr)rrrLrrrr)datesr(r(r)(rand_series_with_duplicate_datetimeindexs           r)rnrorog?g?z2012-01M)freqz period[M]z 2012-02-01Dz period[D]z 2011-01-01rr)unitri)secondsztimedelta64[ns]cCr\rr]r_r(r(r)ea_scalar_and_dtyper$cCr\)zD Fixture for dunder names for common arithmetic operations. r]r_r(r(r)all_arithmetic_operatorsrbr&cCr\)zU Fixture for operator and roperator arithmetic, comparison, and logical ops. r]r_r(r(r)all_binary_operators"r'cCr\)z Fixture for operator and roperator arithmetic functions. Notes ----- This includes divmod and rdivmod, whereas all_arithmetic_operators does not. r]r_r(r(r)all_arithmetic_functionssr)) countrmaxminmeanprodZstdvarZmedianZkurtZskewZsemcCr\)z. Fixture for numeric reduction names. r]r_r(r(r)all_numeric_reductions3rbr0allanycCr\)z. Fixture for boolean reduction names. r]r_r(r(r)all_boolean_reductions>rbr3cCr\)z> Fixture for all (boolean + numeric) reduction names. r]r_r(r(r)all_reductionsIrbr4cCr\)z; Fixture for operator module comparison functions. r]r_r(r(r) comparison_opQr%r5)__le____lt____ge____gt__cCr\)zm Fixture for dunder names for compare operations except == and != * >= * > * < * <= r]r_r(r(r)compare_operators_no_eq_nebrer:)__and____rand____or____ror____xor____rxor__cCr\)zY Fixture for dunder names for common logical operations * | * & * ^ r]r_r(r(r)all_logical_operatorso rA)ZcumsumZcumprodZcumminZcummaxcCr\)z0 Fixture for numeric accumulation names r]r_r(r(r)all_numeric_accumulationsrbrCcCs |dS)zR Returns the configuration for the test setting `--no-strict-data-files`. r#)r=)Z pytestconfigr(r(r)strict_data_filess rDr cCsttjdS)Ntests)r __file__parentr(r(r(r) tests_pathsrHcCs |ddS)Niorr()rHr(r(r)tests_io_data_paths rJCallable[..., str]cs(tjtjtdfdd}|S)aD Get the path to a data file. Parameters ---------- path : str Path to the file, relative to ``pandas/tests/`` Returns ------- path including ``pandas/tests``. Raises ------ ValueError If the path doesn't exist and the --no-strict-data-files option is not set. rEcsJtjjg|R}tj|s#rtd|dtd|d|S)NzCould not find file z' and --no-strict-data-files is not set.zCould not find .)osr-joinexists ValueErrorr3skip)rr-Z BASE_PATHrDr(r)decos  zdatapath..deco)rMr-rNdirnamerF)rDrSr(rRr)datapaths rUcCst|ddddS)z* The iris dataset as a DataFrame. rIrcsvziris.csv)rMZread_csv)rUr(r(r)irissrWz Asia/Tokyozdateutil/US/Pacificzdateutil/Asia/Singaporez+01:15z-02:15z UTC+01:15z UTC-02:15i,i)hoursrrrcCsg|]}t|qSr(rT)rir(r(r)rscCr\)zD Fixture for trying timezones including default (None): {0} r]r_r(r(r)tz_naive_fixturerkrZcCr\)z4 Fixture for trying explicit timezones: {0} r]r_r(r(r)tz_aware_fixturerkr[rz dateutil/UTCcCr\)zQ Fixture to provide variants of UTC timezone strings and tzinfo objects. r]r_r(r(r) utc_fixturerbr\cCr\)zR Parametrized fixture for string dtypes. * str * 'str' * 'U' r]r_r(r(r) string_dtype r]pyarrowcCr\)za Parametrized fixture for string dtypes. * 'string[python]' * 'string[pyarrow]' r]r_r(r(r)nullable_string_dtype r`python pyarrow_numpycCr\)zx Parametrized fixture for pd.options.mode.string_storage. * 'python' * 'pyarrow' * 'pyarrow_numpy' r]r_r(r(r)string_storage-ryrdZnumpy_nullablecCr\)zb Parametrized fixture for pd.options.mode.string_storage. * 'python' * 'pyarrow' r]r_r(r(r) dtype_backend?rarecCr\)zK Parametrized fixture for bytes dtypes. * bytes * 'bytes' r]r_r(r(r) bytes_dtypeSrfcCr\)zN Parametrized fixture for object dtypes. * object * 'object' r]r_r(r(r) object_dtype^rgrhobjectzstring[pyarrow_numpy]cCr\)zo Parametrized fixture for string dtypes. * 'object' * 'string[python]' * 'string[pyarrow]' r]r_r(r(r)any_string_dtypeiryrjcCr\)z\ Parametrized fixture for datetime64 dtypes. * 'datetime64[ns]' * 'M8[ns]' r]r_r(r(r)datetime64_dtype{rgrkcCr\)z^ Parametrized fixture for timedelta64 dtypes. * 'timedelta64[ns]' * 'm8[ns]' r]r_r(r(r)timedelta64_dtypergrlrc CstddddddddS)z- Fixture emits fixed Timestamp.now() irHrIr )rrJrhourminuter microsecond)rr(r(r(r) fixed_now_tssrrcCr\)z^ Parameterized fixture for float dtypes. * float * 'float32' * 'float64' r]r_r(r(r)float_numpy_dtyper^rscCr\)zR Parameterized fixture for float dtypes. * 'Float32' * 'Float64' r]r_r(r(r)float_ea_dtypergrtcCr\)z~ Parameterized fixture for float dtypes. * float * 'float32' * 'float64' * 'Float32' * 'Float64' r]r_r(r(r)any_float_dtyperBrucCr\)zg Parameterized fixture for complex dtypes. * complex * 'complex64' * 'complex128' r]r_r(r(r) complex_dtyper^rvcCr\)z| Parameterized fixture for signed integer dtypes. * int * 'int8' * 'int16' * 'int32' * 'int64' r]r_r(r(r)any_signed_int_numpy_dtyperBrwcCr\)zx Parameterized fixture for unsigned integer dtypes. * 'uint8' * 'uint16' * 'uint32' * 'uint64' r]r_r(r(r)any_unsigned_int_numpy_dtypererxcCr\)z Parameterized fixture for any integer dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' r]r_r(r(r)any_int_numpy_dtyperyrycCr\)z Parameterized fixture for any nullable integer dtype. * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' r]r_r(r(r)any_int_ea_dtyper%rzcCr\)a. Parameterized fixture for any nullable integer dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' r]r_r(r(r) any_int_dtype sr{cCr\)z Parameterized fixture for any nullable integer dtype and any float ea dtypes. * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' * 'Float32' * 'Float64' r]r_r(r(r)any_numeric_ea_dtype$sr|cCr\)a Parameterized fixture for any nullable integer dtype and any float ea dtypes. * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' * 'Float32' * 'Float64' * 'uint8[pyarrow]' * 'int8[pyarrow]' * 'uint16[pyarrow]' * 'int16[pyarrow]' * 'uint32[pyarrow]' * 'int32[pyarrow]' * 'uint64[pyarrow]' * 'int64[pyarrow]' * 'float32[pyarrow]' * 'float64[pyarrow]' r]r_r(r(r)any_numeric_ea_and_arrow_dtype:s r}cCr\)z~ Parameterized fixture for any signed nullable integer dtype. * 'Int8' * 'Int16' * 'Int32' * 'Int64' r]r_r(r(r)any_signed_int_ea_dtype]rer~cCr\)z Parameterized fixture for any (purely) real numeric dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * float * 'float32' * 'float64' r]r_r(r(r)any_real_numpy_dtypejsrcCr\)a  Parameterized fixture for any (purely) real numeric dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * float * 'float32' * 'float64' and associated ea dtypes. r]r_r(r(r)any_real_numeric_dtypesrcCr\)a Parameterized fixture for all numpy dtypes. * bool * 'bool' * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * float * 'float32' * 'float64' * complex * 'complex64' * 'complex128' * str * 'str' * 'U' * bytes * 'bytes' * 'datetime64[ns]' * 'M8[ns]' * 'timedelta64[ns]' * 'm8[ns]' * object * 'object' r]r_r(r(r)any_numpy_dtyper(rcCr\)a Parameterized fixture for all numeric dtypes. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * float * 'float32' * 'float64' * complex * 'complex64' * 'complex128' * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' * 'Float32' * 'Float64' r]r_r(r(r)any_numeric_dtypesrrrmixedbytesacrz mixed-integerg@Zfloatingrintegerzmixed-integer-floatdecimal datetime64z 2013-01-01z 2018-01-01rZ20180101riicomplexy??y@@rrcCs |j\}}tj|td}||fS)a Fixture for all inferred dtypes from _libs.lib.infer_dtype The covered (inferred) types are: * 'string' * 'empty' * 'bytes' * 'mixed' * 'mixed-integer' * 'mixed-integer-float' * 'floating' * 'integer' * 'decimal' * 'boolean' * 'datetime64' * 'datetime' * 'date' * 'timedelta' * 'time' * 'period' * 'interval' Returns ------- inferred_dtype : str The string for the inferred dtype from _libs.lib.infer_dtype values : np.ndarray An array of object dtype that will be inferred to have `inferred_dtype` Examples -------- >>> from pandas._libs import lib >>> >>> def test_something(any_skipna_inferred_dtype): ... inferred_dtype, values = any_skipna_inferred_dtype ... # will pass ... assert lib.infer_dtype(values, skipna=True) == inferred_dtype r)r^rLrri)r`Zinferred_dtyperr(r(r)any_skipna_inferred_dtypes )rcCs>tjdddddlm}ddlm}|}d|j_||dS) zj Get an instance of IPython.InteractiveShell. Will raise a skip if IPython is not installed. ZIPythonz6.0.0)Z minversionr)InteractiveShell)Configz:memory:)r?)r3 importorskipZIPython.core.interactiveshellrZtraitlets.configrZHistoryManagerZ hist_file)rrrr(r(r)ip/s    r)ZbsrZcooZcscZcsrZdiaZdokZlilcCstd}t||jdS)z- Yields scipy sparse matrix classes. z scipy.sparseZ_matrix)r3rgetattrr^)r`sparser(r(r)spmatrixBs rcCs6g|]}tttj|tjjr|dkrttj|qS)Tick) issubclassrrMoffsetsr)ror(r(r)rMs cCr\)zN Fixture for Tick based datetime offsets available for a time series. r]r_r(r(r) tick_classesLrBrcCs|Srr(rVr(r(r)rXZscCr\)zk Simple fixture for testing keys in sorting methods. Tests None (no key) and the identity key. r]r_r(r(r) sort_by_keyZrkrccsztdddlm}ddlm}ddlm}Gddd|}|d|d d |V|ddd|j d<|j dS) Nfsspecr)register_implementation)MemoryFileSystem) _registrycs(eZdZdZdgZdfdd ZZS)z fsspectest..TestMemoryFStestmemNr!r"cs(|dd|jd<tjdi|dS)Ntestrr()poprsuperr)rr __class__r(r)rnsz)fsspectest..TestMemoryFS.__init__r)rrrprotocolrr __classcell__r(r(rr) TestMemoryFSjsrrT)clobber) r3rrrZfsspec.implementations.memoryrZfsspec.registryrrrstoreclear)rrregistryrr(r(r) fsspectestcs      r)rNN)ZEgonZVenkmanN)NCC1701Drr#tuple[Hashable, Hashable, Hashable]cCr\)zP A 3-tuple of names, the first two for operands, the last for a result. r]r_r(r(r)rysrcCr\)zI Parametrize over __setitem__, loc.__setitem__, iloc.__setitem__ r]r_r(r(r) indexer_slirbrcCr\)z< Parametrize over loc.__getitem__, iloc.__getitem__ r]r_r(r(r) indexer_lirbrcCr\)z8 Parametrize over __setitem__, iloc.__setitem__ r]r_r(r(r) indexer_sirbrcCr\)z7 Parametrize over __setitem__, loc.__setitem__ r]r_r(r(r) indexer_slrbrcCr\)z: Parametrize over at.__setitem__, loc.__setitem__ r]r_r(r(r) indexer_alrbrcCr\)z< Parametrize over iat.__setitem__, iloc.__setitem__ r]r_r(r(r) indexer_ialrbrboolcCstjjjdkS)z> Fixture to check if the array manager is being used. r)rMoptionsmode data_managerr(r(r(r)using_array_managersrcCstjjjo tjjjdkS)z7 Fixture to check if Copy-on-Write is enabled. block)rMrrZ copy_on_writerr(r(r(r)using_copy_on_writesrz Europe/Warsawzdateutil/Europe/WarsawcCr\)zE tzinfo for Europe/Warsaw using pytz, dateutil, or zoneinfo. r]r_r(r(r)warsawrbrcCsdS)N)r_rcr(r(r(r(r)arrow_string_storagesrr)r+r,r-r.r/r.r!r")r!r)r!r)r!r)r!r )rDr.r!rK)r!r)r!r)r!r)r!r.(>__doc__ __future__r collectionsrrrrrrrr operatorrMpathlibr typingr r Z dateutil.tzr rZ hypothesisrstnumpyrLr3ZpytzrrZpandas.util._test_decoratorsutilZ_test_decoratorstdZpandas.core.dtypes.dtypesrrZpandasrMrrrrrrZpandas._testingZ_testingrZ pandas.corerZpandas.core.indexes.apirrZpandas.util.versionrcollections.abcrrr_pa ImportErrorZ has_pyarrowZzoneinfoZZoneInfoZZoneInfoNotFoundErrorr*r6r@Z HealthCheckZtoo_slowZhypothesis_health_checks __version__appendZdiffering_executorssettingsZregister_profiletupleZ load_profilesplitr0rZtseriesrclsZregister_type_strategyZbuildsZintegersZbooleansZfixturer<rOraZ axis_framercrdrfrgrjrprqrrr^Z skip_if_norxrzr{r~rZ NULL_OBJECTSrZnulls_fixture2rZNaTrZunique_nulls_fixture2ZNP_NAT_OBJECTSrZnp_nat_fixture2rrZindex_or_series2rrrZbox_with_array2rrrrrrrZmakeStringIndexZ makeDateIndexZmakePeriodIndexZmakeTimedeltaIndexZmakeRangeIndexZ makeIntIndexZ makeUIntIndexZmakeFloatIndexZ makeBoolIndexrrirrrZmakeNumericIndexZmakeCategoricalIndexZmakeIntervalIndexrrurrridxkeysrPZindex_fixture2r>rZ index_flat2rrrrrZ_seriesrr ZNARROW_NP_DTYPESZ_narrow_seriesrrZPYTHON_DATA_TYPESZ_typ_objects_seriesrrrrrrrr$Zarithmetic_dunder_methodsr&addZraddsubZrsubmulZrmultruedivZrtruedivfloordivZ rfloordivmodZrmodpowZrpoweqneltlegtgeand_Zrand_xorZrxoror_Zror_r'r)Z_all_numeric_reductionsr0Z_all_boolean_reductionsr3Z_all_reductionsr4r5r:rAZ_all_numeric_accumulationsrCrDrHrJrUrWZ TIMEZONESextendZ TIMEZONE_IDSZparametrize_fixture_docr.rZr[Ztz_aware_fixture2Z_UTCSr\Z utc_fixture2Z STRING_DTYPESr]r`rdreZstring_storage2Z BYTES_DTYPESrfZ OBJECT_DTYPESrhrjZDATETIME64_DTYPESrkZTIMEDELTA64_DTYPESrlrrZFLOAT_NUMPY_DTYPESrsZFLOAT_EA_DTYPESrtZALL_FLOAT_DTYPESruZCOMPLEX_DTYPESrvZSIGNED_INT_NUMPY_DTYPESrwZUNSIGNED_INT_NUMPY_DTYPESrxZALL_INT_NUMPY_DTYPESryZALL_INT_EA_DTYPESrzZALL_INT_DTYPESr{r|ZALL_INT_PYARROW_DTYPES_STR_REPRZFLOAT_PYARROW_DTYPES_STR_REPRr}ZSIGNED_INT_EA_DTYPESr~ZALL_REAL_NUMPY_DTYPESrZALL_REAL_DTYPESrZALL_NUMPY_DTYPESrZALL_NUMERIC_DTYPESrZNArZ_any_skipna_inferred_dtyper[_rrr__all__rrrrsetitemlocr rrrratrZiatrrrZwarsawsrrr(r(r(r)sj              @                                                "                          !                        $#$$2