o
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ZejRdddZejRdddZejRdddZdddddddddde e ededede	je	ed*de	eddddgZe=durGeߠe=>de=>dg dd eD Ze"eeejReed:d d! Ze"eed*d ejRed*d ed*d d:d"d# ZeZd$d%ee e	jgZe=duree=>d ejRedBd&d' ZeZejRe0jdBd(d) ZejRdej_de"`d*d[gdBd+d, ZejRd-ej_d*e"`d*d[ej_d.e"`d*d[gdBd/d0 ZejRd1ej_d*e"`d*d[gdBd2d3 ZeZejRe0jdBd4d5 ZejRe0jdBd6d7 ZejRd8dej_de"`d*d[ej_d9e"`d*d[gdBd:d; ZejRe0jdBd<d= ZejRe0jdBd>d? ZejRddAdBZejRe0jdBdCdD ZejRe0jdBdEdF ZejRe0jdBdGdH Z ejRe0jdBdIdJ ZejRe0jdBdKdL ZejRe0jdBdMdN ZejRe0jdBdOdP ZejRe0j	dBdQdR Z
ejRe0jdBdSdT ZejRe0j	e0j dBdUdV ZejRe0j	e0j e0j e0j dBdWdX ZejRe0jdBdYdZ ZejRe0jdBd[d\ ZejRe0jdBd]d^ ZejRe0jdBd_d` ZejRe0jdBdadb Zddcejiddgfddce'jddgfdedce'jjddgfdfdgejidhgfdiejiejiejigfdig fdjdcejidgfdedcejidkgfdldmejidkgfdnd*ejidgfdod*ejidkgfdped*ejiedgfddejidgfdde'jdgfdqedrejiedsgfde-dtejie-dugfdvedwd*d*ejiedxd*d*gfdydzejid{gfded*ejiedgfd|ed*ejiedgfde*dwe'jje*dxgfd}e)dd*ejie)ddgfgZee \ZZejReed:d~d Z ejRdd Z!ejRg ddBdd Z"ejRdd e'jLj#D dBdd Z$ejRddd9 gdBdd Z%eR dd Z&ejRdddejiejiejifejie'jjdfejie'jdfe'je'je'jfgdBdddZ'ejRe0j(e0j)e0j*gdBdd Z+ejRe0j)e0j*gdBdd Z,ejRe0j(e0j*gdBdd Z-ejRe0j(e0j)gdBdd Z.ejRe0j/e0j)gdBdd Z0ejRe0j1e0j*gdBdd Z2ejRdddZ3ejRdddZ4ddgZ5e=du
re5e=>d ejRe5dBdddZ6eR dd Z7dS (  a  
This file is very long and growing, but it was decided to not split it yet, as
it's still manageable (2020-03-17, ~1.1k LoC). See gh-31989

Instead of splitting it was decided to define sections here:
- Configuration / Settings
- Autouse fixtures
- Common arguments
- Missing values & co.
- Classes
- Indices
- Series'
- DataFrames
- Operators & Operations
- Data sets/files
- Time zones
- Dtypes
- Misc
    )annotations)abc)datedatetimetime	timedeltatimezone)DecimalN)Path)TYPE_CHECKINGCallable)tzlocaltzutc)
strategies)FixedOffsetutc)DatetimeTZDtypeIntervalDtype)	DataFrameIntervalPeriodSeries	Timedelta	Timestamp)ops)Index
MultiIndex)HashableIteratorFTUTCreturnNonec                 C  s   | j dddd d S )N--no-strict-data-filesstore_falsez6Don't fail if a test is skipped for missing data file.)actionhelp)Z	addoption)parser r'   ?D:\Projects\ConvertPro\env\Lib\site-packages\pandas/conftest.pypytest_addoptiong   s
   
r)   itempytest.Itempathstrmessagec                 C  s,   | j |r| tjd|  dS dS )a  Ignore doctest warning.

    Parameters
    ----------
    item : pytest.Item
        pytest test item.
    path : str
        Module path to Python object, e.g. "pandas.core.frame.DataFrame.append". A
        warning will be filtered when item.name ends with in given path. So it is
        sufficient to specify e.g. "DataFrame.append".
    message : str
        Message to be filtered.
    zignore:N)nameendswith
add_markerpytestmarkfilterwarnings)r*   r,   r.   r'   r'   r(   ignore_doctest_warningo   s   r5   c                 C  sv   | dp|j ddd}g d}| D ]&}|r,|tjd |D ]
\}}t||| q!d|jv r8|tjj qd S )Nz--doctest-modulesz--doctest-cythonF)default))Zis_int64_dtypezis_int64_dtype is deprecated)Zis_interval_dtypezis_interval_dtype is deprecated)Zis_period_dtypezis_period_dtype is deprecated)Zis_datetime64tz_dtypez#is_datetime64tz_dtype is deprecated)Zis_categorical_dtypez"is_categorical_dtype is deprecated)Z	is_sparsezis_sparse is deprecated)NDFrame.replacezThe 'method' keyword)r7   zSeries.replace without 'value')zSeries.idxminThe behavior of Series.idxmin)zSeries.idxmaxThe behavior of Series.idxmax)zSeriesGroupBy.idxminr8   )zSeriesGroupBy.idxmaxr9   )zmissing.mask_zero_div_zerozdivide by zero encountered)Zto_pydatetimez>The 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)zResampler.fillnaz+DatetimeIndexResampler.fillna is deprecated)DataFrameGroupBy.fillnaz3DataFrameGroupBy.fillna with 'method' is deprecated)r:   z,DataFrame.fillna with 'method' is deprecatedadd_doctest_importsz/frame/)	getoptionr1   r2   r3   Zusefixturesr5   ZnodeidZarraymanager)itemsconfigZ
is_doctestZignored_doctest_warningsr*   r,   r.   r'   r'   r(   pytest_collection_modifyitems   s   +
r?   ci)deadlineZsuppress_health_checkz)MonthBegin MonthEnd BMonthBegin BMonthEndic   )n	normalizez%YearBegin YearEnd BYearBegin BYearEnd         )Z	min_valueZ	max_value)rC   rD   monthz1QuarterBegin QuarterEnd BQuarterBegin BQuarterEndi   )rC   rD   ZstartingMonthc                 C  s   t | d< t| d< dS )z:
    Make `np` and `pd` names available for doctests.
    nppdN)rK   rL   )Zdoctest_namespacer'   r'   r(   r;      s   r;   )Zautousec                   C  s   t dd dS )z<
    Configure settings for all tests and test modules.
    Zchained_assignmentraiseN)rL   Z
set_optionr'   r'   r'   r(   configure_tests   s   rN   )r   rG   indexcolumnsc                 C     dt |  S Nzaxis=reprxr'   r'   r(   <lambda>      rW   )paramsidsc                 C     | j S )z@
    Fixture for returning the axis numbers of a DataFrame.
    paramrequestr'   r'   r(   axis     r`   rP   c                 C  rQ   rR   rS   rU   r'   r'   r(   rW     rX   c                 C  r[   )zA
    Fixture for returning aliases of axis 1 of a DataFrame.
    r\   r^   r'   r'   r(   axis_1  ra   rb   )TFN)rY   c                 C  r[   )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     
rc   c                 C  r[   )z6
    Boolean 'ordered' parameter for Categorical.
    r\   r^   r'   r'   r(   ordered(  ra   re   c                 C  r[   )z%
    Boolean 'skipna' parameter.
    r\   r^   r'   r'   r(   skipna0  ra   rf   )firstlastFc                 C  r[   )z[
    Valid values for the 'keep' parameter used in
    .duplicated or .drop_duplicates
    r\   r^   r'   r'   r(   keep8     ri   )bothneitherleftrightc                 C  r[   )zA
    Fixture for trying all interval 'inclusive' parameters.
    r\   r^   r'   r'   r(   inclusive_endpoints_fixtureA  ra   ro   )rm   rn   rk   rl   c                 C  r[   )z<
    Fixture for trying all interval closed parameters.
    r\   r^   r'   r'   r(   closedI  ra   rp   c                 C  r[   )zS
    Secondary closed fixture to allow parametrizing over all pairs of closed.
    r\   r^   r'   r'   r(   other_closedQ  ra   rq   gzipbz2zipxztarZzstdZ	zstandard)Zmarksc                 C  r[   )zK
    Fixture for trying common compression types in compression tests.
    r\   r^   r'   r'   r(   compressionY     rw   c                 C  r[   )zk
    Fixture for trying common compression types in compression tests excluding
    uncompressed case.
    r\   r^   r'   r'   r(   compression_onlyk  rx   ry   c                 C  r[   )z,
    Fixture that an array is writable.
    r\   r^   r'   r'   r(   writable}  ra   rz   )innerouterrm   rn   c                 C  r[   )z:
    Fixture for trying all types of join operations.
    r\   r^   r'   r'   r(   	join_type  ra   r}   nlargest	nsmallestc                 C  r[   )z1
    Fixture for trying all nselect methods.
    r\   r^   r'   r'   r(   nselect_method  ra   r   c                 C  
   t | jS Ntype__name__rU   r'   r'   r(   rW        
 c                 C  r[   )z/
    Fixture for each null type in pandas.
    r\   r^   r'   r'   r(   nulls_fixture  ra   r   c                 C  r[   )zL
    Fixture for each null type in pandas, each null type exactly once.
    r\   r^   r'   r'   r(   unique_nulls_fixture  ra   r   c                 C  r   r   r   rU   r'   r'   r(   rW     r   c                 C  r[   )z-
    Fixture for each NaT type in numpy.
    r\   r^   r'   r'   r(   np_nat_fixture  ra   r   c                 C  r[   )z;
    Fixture to parametrize over DataFrame and Series.
    r\   r^   r'   r'   r(   frame_or_series  ra   r   rO   seriesc                 C  r[   )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_series  rd   r   )rO   r   arrayc                 C  r[   )zG
    Fixture to parametrize over Index, Series, and ExtensionArray
    r\   r^   r'   r'   r(   index_or_series_or_array  ra   r   c                 C  r[   r   )r   rU   r'   r'   r(   rW         c                 C  r[   )z]
    Fixture to test behavior for Index, Series, DataFrame, and pandas Array
    classes
    r\   r^   r'   r'   r(   box_with_array  rj   r   c                  C  s   G dd dt } | S )z,
    Fixture for a dictionary subclass.
    c                   @  s   e Zd ZdddZdS )z"dict_subclass.<locals>.TestSubDictr    r!   c                 _  s   t j| g|R i | d S r   )dict__init__)selfargskwargsr'   r'   r(   r     s   z+dict_subclass.<locals>.TestSubDict.__init__Nr    r!   )r   
__module____qualname__r   r'   r'   r'   r(   TestSubDict  s    r   )r   )r   r'   r'   r(   dict_subclass  s   r   c                  C  s   G dd dt j} | S )z8
    Fixture for a non-mapping dictionary subclass.
    c                   @  s2   e Zd ZdddZdd Zddd	ZdddZdS )z5non_dict_mapping_subclass.<locals>.TestNonDictMappingr    r!   c                 S  s
   || _ d S r   )_data)r   Zunderlying_dictr'   r'   r(   r        
z>non_dict_mapping_subclass.<locals>.TestNonDictMapping.__init__c                 S  s   | j |S r   )r   __getitem__)r   keyr'   r'   r(   r     s   zAnon_dict_mapping_subclass.<locals>.TestNonDictMapping.__getitem__r   c                 S  
   | j  S r   )r   __iter__r   r'   r'   r(   r     r   z>non_dict_mapping_subclass.<locals>.TestNonDictMapping.__iter__intc                 S  r   r   )r   __len__r   r'   r'   r(   r   
  r   z=non_dict_mapping_subclass.<locals>.TestNonDictMapping.__len__Nr   )r    r   )r    r   )r   r   r   r   r   r   r   r'   r'   r'   r(   TestNonDictMapping   s
    

r   )r   Mapping)r   r'   r'   r(   non_dict_mapping_subclass  s   r   c                  C  s^   t d} | dd dd dd g }|jdd |jjD |_|jjg dd	d
 |S )z
    DataFrame with 3 level MultiIndex (year, month, day) covering
    first 100 business days from 2000-01-01 with random data
    d   c                 S  r[   r   )yearrU   r'   r'   r(   rW     r   zAmultiindex_year_month_day_dataframe_random_data.<locals>.<lambda>c                 S  r[   r   )rI   rU   r'   r'   r(   rW     r   c                 S  r[   r   )dayrU   r'   r'   r(   rW     r   c                 S  s   g | ]}| d qS )i8)astype).0Zlevr'   r'   r(   
<listcomp>  s    zCmultiindex_year_month_day_dataframe_random_data.<locals>.<listcomp>)r   rI   r   T)Zinplace)tmZmakeTimeDataFramegroupbysumrO   Z
set_levelslevelsZ	set_names)ZtdfZymdr'   r'   r(   /multiindex_year_month_day_dataframe_random_data  s
   
 r   r   c                   C  s*   t g dg dgg dg dgddgdS )z;
    2-level MultiIndex, lexsorted, with string names.
    foobarbazquxonetwothree)
r   r   r   rG   rG      r      r   r   )
r   rG   r   r   rG   rG   r   r   rG   r   rg   second)r   codesnames)r   r'   r'   r'   r(   %lexsorted_two_level_string_multiindex!  s
   r   r   c                 C  s,   | }t tjdd|tg ddddS )z2DataFrame with 2 level MultiIndex with random datar   )
   r   )ABCexpr/   )rO   rP   )r   rK   randomdefault_rngstandard_normalr   )r   rO   r'   r'   r(    multiindex_dataframe_random_data-  s   r   c                  C  sT   t g d} t ddg}tg d}tg d}ddg}t| |g||g|dd	S )
zJ
    MultiIndex used to test the general functionality of this object
    r   r   r   )r   r   rG   r   r   r   )r   rG   r   rG   r   rG   rg   r   F)r   r   r   Zverify_integrity)r   rK   r   r   )Z
major_axisZ
minor_axisZmajor_codesZminor_codesZindex_namesr'   r'   r(   _create_multiindex:  s   r   c                   C  s,   t jddgddgtjddddgg d	d
S )zB
    MultiIndex with a level that is a tzaware DatetimeIndex.
    rG   r   ab20130101r   
US/Eastern)Zperiodstzr   )r   )r   Zfrom_productrL   Z
date_ranger'   r'   r'   r(   _create_mi_with_dt64tz_levelN  s   r   stringr   r   zdatetime-tzz
US/Pacific)r   Zperiodr   rangeZint8dtypeZint16int32int64Zuint8Zuint16Zuint32Zuint64float32Zfloat64zbool-objectr   r   	complex64
complex128)r   r   r   )rG   r   r   )r   r   rG   rG   r   r   ZInt64ZUInt16ZFloat32booleanzstring[python])
bool-dtyper   r   Zcategoricalintervalemptytuplesmi-with-dt64tz-levelmultirepeatsZnullable_intZnullable_uintZnullable_floatZnullable_boolzstring-pythonzstring[pyarrow]zstring-pyarrowc                 C  s   t | j  S )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(   rO     s   c                 C  s   g | ]\}}t |ts|qS r'   )
isinstancer   r   r   valuer'   r'   r(   r     s
    r   c                 C  s   | j }t|  S )z8
    index fixture, but excluding MultiIndex cases.
    )r]   r   r   )r_   r   r'   r'   r(   
index_flat  s   	r   c                 C  s0   g | ]\}}| d s|dv st|ts|qS ))r   Zuintfloat)r   r   r   r   )
startswithr   r   r   r'   r'   r(   r     s    c                 C  s   t | j jdd}|j }| jdv r4| }d|d dd  |d< d|d dd  |d< t|S d|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.
    Tdeep)r   r   r   r   r   rG   N)r   r]   r   valuestolistr   from_tuplesr   )r_   indvalsr'   r'   r(   index_with_missing  s   


r   r   c                  C     t  } d| _| S )zC
    Fixture for Series of floats with Index of unique strings
    r   )r   ZmakeStringSeriesr/   sr'   r'   r(   string_series     r   c                  C  r   )zI
    Fixture for Series of dtype object with Index of unique strings
    objects)r   ZmakeObjectSeriesr/   r   r'   r'   r(   object_series  r   r   c                  C  r   )z9
    Fixture for Series of floats with DatetimeIndex
    ts)r   ZmakeTimeSeriesr/   r   r'   r'   r(   datetime_series  r   r   c                 C  s*   t | }tjd|}t|| dddS )zHelper for the _series dictr   r   F)rO   r/   r   )lenrK   r   r   r   r   )rO   sizedatar'   r'   r(   _create_series  s   r  c                 C  s"   i | ]\}}d | dt |qS )zseries-with-z-indexr  )r   Zindex_idrO   r'   r'   r(   
<dictcomp>  s    r  c                 C  s   t | S )zE
    Fixture for tests on series with changing types of indices.
    r  rO   r'   r'   r(   series_with_simple_index  s   r  c                  C  sP   g dg dg} t |  }t|}tjdd}t||d}tj|j	d< |S )z:
    Fixture with a Series with a 2-level MultiIndex.
    )r   r   r   r   r   r   r   r   )r   r   r   r   r   r   r   r   r      r  r   )
rt   r   r   rK   r   r   r   r   naniloc)Zarraysr   rO   r   Zserr'   r'   r(   series_with_multilevel_index  s   
r	  c                 C  s$   i | ]}|j  d tjd|dqS )-seriesr   )r/   r   )r   r   Zmake_rand_seriesr   r   r'   r'   r(   r    s    c                 C     t | j jddS )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]   r   r^   r'   r'   r(   index_or_series_obj  s   r  c                 C  s   i | ]}|j  d t|qS )r
  )r   r   r  r'   r'   r(   r  "  s    c                 C  r  )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]   r   r^   r'   r'   r(   index_or_series_memory_obj/  s   r  c                   C  s   t t dS )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   )r   r   getSeriesDatar   r'   r'   r'   r(   	int_frame<  s   r  c                   C     t t S )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]
    )r   r   ZgetTimeSeriesDatar'   r'   r'   r(   datetime_frameY     r  c                   C  r  )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]
    )r   r   r  r'   r'   r'   r(   float_framev  r  r  c                	   C  s>   t dddtjdgd ddtjdgd ddd	tdd
S )z
    Fixture for DataFrame of float/int/string columns with RangeIndex
    Columns are ['a', 'b', 'c', 'float32', 'int32'].
          ?r   r   r   r   r   rG   r   )r   r   cr   r   r  )r   rK   r   aranger'   r'   r'   r(   mixed_type_frame  s   r  c                  C  s   t dddt dddt dddt dddt dddt dddt dddt dddt dddt dddg
} ttjdt| | dS )zF
    Fixture for Series with a DatetimeIndex that has duplicates.
    i  rG   r   r      rF   r  )r   r   rK   r   r   r   r   )datesr'   r'   r(   (rand_series_with_duplicate_datetimeindex  s   









r  )rm   rn   rn   g?g      ?z2012-01M)freqz	period[M]z
2012-02-01Dz	period[D]z
2011-01-01r   r   )unitr   i  )secondsztimedelta64[ns]c                 C  r[   r   r\   r^   r'   r'   r(   ea_scalar_and_dtype     r#  c                 C  r[   )zD
    Fixture for dunder names for common arithmetic operations.
    r\   r^   r'   r'   r(   all_arithmetic_operators  ra   r%  c                 C  r[   )zU
    Fixture for operator and roperator arithmetic, comparison, and logical ops.
    r\   r^   r'   r'   r(   all_binary_operators     "r&  c                 C  r[   )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_functions   s   r(  )countr   maxminmeanprodZstdvarZmedianZkurtZskewZsemc                 C  r[   )z.
    Fixture for numeric reduction names.
    r\   r^   r'   r'   r(   all_numeric_reductions.  ra   r/  allanyc                 C  r[   )z.
    Fixture for boolean reduction names.
    r\   r^   r'   r'   r(   all_boolean_reductions9  ra   r2  c                 C  r[   )z>
    Fixture for all (boolean + numeric) reduction names.
    r\   r^   r'   r'   r(   all_reductionsD  ra   r3  c                 C  r[   )z;
    Fixture for operator module comparison functions.
    r\   r^   r'   r'   r(   comparison_opL  r$  r4  )__le____lt____ge____gt__c                 C  r[   )zm
    Fixture for dunder names for compare operations except == and !=

    * >=
    * >
    * <
    * <=
    r\   r^   r'   r'   r(   compare_operators_no_eq_ne]  rd   r9  )__and____rand____or____ror____xor____rxor__c                 C  r[   )zY
    Fixture for dunder names for common logical operations

    * |
    * &
    * ^
    r\   r^   r'   r'   r(   all_logical_operatorsj     r@  )ZcumsumZcumprodZcumminZcummaxc                 C  r[   )z0
    Fixture for numeric accumulation names
    r\   r^   r'   r'   r(   all_numeric_accumulations{  ra   rB  c                 C  s
   |  dS )zR
    Returns the configuration for the test setting `--no-strict-data-files`.
    r"   )r<   )Zpytestconfigr'   r'   r(   strict_data_files  s   
rC  r
   c                   C  s   t tjd S )Ntests)r
   __file__parentr'   r'   r'   r(   
tests_path  s   rG  c                 C  s   | d d S )Nior   r'   )rG  r'   r'   r(   tests_io_data_path  s   rI  Callable[..., str]c                   s(   t jt jtd  fdd}|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.
    rD  c                    sJ   t jj g| R  }t j|s#rtd| dtd| d |S )NzCould not find file z' and --no-strict-data-files is not set.zCould not find .)osr,   joinexists
ValueErrorr2   skip)r   r,   Z	BASE_PATHrC  r'   r(   deco  s   
zdatapath.<locals>.deco)rL  r,   rM  dirnamerE  )rC  rR  r'   rQ  r(   datapath  s   
rT  c                 C  s   t | ddddS )z*
    The iris dataset as a DataFrame.
    rH  r   csvziris.csv)rL   Zread_csv)rT  r'   r'   r(   iris  s   rV  z
Asia/Tokyozdateutil/US/Pacificzdateutil/Asia/Singaporez+01:15z-02:15z	UTC+01:15z	UTC-02:15i,  i)hoursr   r   r   c                 C  s   g | ]}t |qS r'   rS   )r   ir'   r'   r(   r     s    c                 C  r[   )zD
    Fixture for trying timezones including default (None): {0}
    r\   r^   r'   r'   r(   tz_naive_fixture  rj   rY  c                 C  r[   )z4
    Fixture for trying explicit timezones: {0}
    r\   r^   r'   r'   r(   tz_aware_fixture  rj   rZ  r   zdateutil/UTCc                 C  r[   )zQ
    Fixture to provide variants of UTC timezone strings and tzinfo objects.
    r\   r^   r'   r'   r(   utc_fixture  ra   r[  c                 C  r[   )zR
    Parametrized fixture for string dtypes.

    * str
    * 'str'
    * 'U'
    r\   r^   r'   r'   r(   string_dtype     	r\  pyarrowc                 C  r[   )za
    Parametrized fixture for string dtypes.

    * 'string[python]'
    * 'string[pyarrow]'
    r\   r^   r'   r'   r(   nullable_string_dtype     r_  pythonpyarrow_numpyc                 C  r[   )zx
    Parametrized fixture for pd.options.mode.string_storage.

    * 'python'
    * 'pyarrow'
    * 'pyarrow_numpy'
    r\   r^   r'   r'   r(   string_storage(  rx   rc  Znumpy_nullablec                 C  r[   )zb
    Parametrized fixture for pd.options.mode.string_storage.

    * 'python'
    * 'pyarrow'
    r\   r^   r'   r'   r(   dtype_backend:  r`  rd  c                 C  r[   )zK
    Parametrized fixture for bytes dtypes.

    * bytes
    * 'bytes'
    r\   r^   r'   r'   r(   bytes_dtypeN     re  c                 C  r[   )zN
    Parametrized fixture for object dtypes.

    * object
    * 'object'
    r\   r^   r'   r'   r(   object_dtypeY  rf  rg  objectzstring[pyarrow_numpy]c                 C  r[   )zo
    Parametrized fixture for string dtypes.
    * 'object'
    * 'string[python]'
    * 'string[pyarrow]'
    r\   r^   r'   r'   r(   any_string_dtyped  rx   ri  c                 C  r[   )z\
    Parametrized fixture for datetime64 dtypes.

    * 'datetime64[ns]'
    * 'M8[ns]'
    r\   r^   r'   r'   r(   datetime64_dtypev  rf  rj  c                 C  r[   )z^
    Parametrized fixture for timedelta64 dtypes.

    * 'timedelta64[ns]'
    * 'm8[ns]'
    r\   r^   r'   r'   r(   timedelta64_dtype  rf  rk  r   c                	   C  s   t ddddddddS )z-
    Fixture emits fixed Timestamp.now()
    i  rG   rH   r        )r   rI   r   hourminuter   microsecond)r   r'   r'   r'   r(   fixed_now_ts  s   rq  c                 C  r[   )z^
    Parameterized fixture for float dtypes.

    * float
    * 'float32'
    * 'float64'
    r\   r^   r'   r'   r(   float_numpy_dtype  r]  rr  c                 C  r[   )zR
    Parameterized fixture for float dtypes.

    * 'Float32'
    * 'Float64'
    r\   r^   r'   r'   r(   float_ea_dtype  rf  rs  c                 C  r[   )z~
    Parameterized fixture for float dtypes.

    * float
    * 'float32'
    * 'float64'
    * 'Float32'
    * 'Float64'
    r\   r^   r'   r'   r(   any_float_dtype  rA  rt  c                 C  r[   )zg
    Parameterized fixture for complex dtypes.

    * complex
    * 'complex64'
    * 'complex128'
    r\   r^   r'   r'   r(   complex_dtype  r]  ru  c                 C  r[   )z|
    Parameterized fixture for signed integer dtypes.

    * int
    * 'int8'
    * 'int16'
    * 'int32'
    * 'int64'
    r\   r^   r'   r'   r(   any_signed_int_numpy_dtype  rA  rv  c                 C  r[   )zx
    Parameterized fixture for unsigned integer dtypes.

    * 'uint8'
    * 'uint16'
    * 'uint32'
    * 'uint64'
    r\   r^   r'   r'   r(   any_unsigned_int_numpy_dtype  rd   rw  c                 C  r[   )z
    Parameterized fixture for any integer dtype.

    * int
    * 'int8'
    * 'uint8'
    * 'int16'
    * 'uint16'
    * 'int32'
    * 'uint32'
    * 'int64'
    * 'uint64'
    r\   r^   r'   r'   r(   any_int_numpy_dtype  rx   rx  c                 C  r[   )z
    Parameterized fixture for any nullable integer dtype.

    * 'UInt8'
    * 'Int8'
    * 'UInt16'
    * 'Int16'
    * 'UInt32'
    * 'Int32'
    * 'UInt64'
    * 'Int64'
    r\   r^   r'   r'   r(   any_int_ea_dtype  r$  ry  c                 C  r[   )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  s   rz  c                 C  r[   )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  s   r{  c                 C  r[   )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_dtype5  s    r|  c                 C  r[   )z~
    Parameterized fixture for any signed nullable integer dtype.

    * 'Int8'
    * 'Int16'
    * 'Int32'
    * 'Int64'
    r\   r^   r'   r'   r(   any_signed_int_ea_dtypeX  rd   r}  c                 C  r[   )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_dtypee  s   r~  c                 C  r[   )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_dtypez  s   r  c                 C  r[   )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_dtype  r'  r  c                 C  r[   )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_dtype  s   r  r   r  mixedbytes   a   cr   zmixed-integerg       @Zfloatingr  integerzmixed-integer-floatdecimal
datetime64z
2013-01-01z
2018-01-01r   Z20180101r   i  i  complexy      ?      ?y       @       @r   r   c                 C  s    | j \}}tj|td}||fS )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]   rK   r   rh  )r_   Zinferred_dtyper   r'   r'   r(   any_skipna_inferred_dtype  s   
)r  c                  C  s>   t jddd ddlm}  ddlm} | }d|j_| |dS )	zj
    Get an instance of IPython.InteractiveShell.

    Will raise a skip if IPython is not installed.
    ZIPythonz6.0.0)Z
minversionr   )InteractiveShell)Configz:memory:)r>   )r2   importorskipZIPython.core.interactiveshellr  Ztraitlets.configr  ZHistoryManagerZ	hist_file)r  r  r  r'   r'   r(   ip*  s   
r  )ZbsrZcooZcscZcsrZdiaZdokZlilc                 C  s   t d}t|| jd S )z-
    Yields scipy sparse matrix classes.
    zscipy.sparseZ_matrix)r2   r  getattrr]   )r_   sparser'   r'   r(   spmatrix=  s   
r  c                 C  s6   g | ]}t ttj|tjjr|d krttj|qS )Tick)
issubclassr  rL   offsetsr  )r   or'   r'   r(   r   H  s    
c                 C  r[   )zN
    Fixture for Tick based datetime offsets available for a time series.
    r\   r^   r'   r'   r(   tick_classesG  rA  r  c                 C  s   | S r   r'   rU   r'   r'   r(   rW   U  s    c                 C  r[   )zk
    Simple fixture for testing keys in sorting methods.
    Tests None (no key) and the identity key.
    r\   r^   r'   r'   r(   sort_by_keyU  rj   r  c                  c  sz    t d ddlm}  ddlm} ddlm} G dd d|}| d|d	d
 | V  |dd  d |j	d< |j
  d S )Nfsspecr   )register_implementation)MemoryFileSystem)	_registryc                      s(   e Zd ZdZdgZd fddZ  ZS )z fsspectest.<locals>.TestMemoryFStestmemNr    r!   c                   s(   | dd | jd< t jdi | d S )Ntestr   r'   )popr  superr   )r   r   	__class__r'   r(   r   i  s   z)fsspectest.<locals>.TestMemoryFS.__init__r   )r   r   r   protocolr  r   __classcell__r'   r'   r  r(   TestMemoryFSe  s    r  r  T)clobber)r2   r  r  r  Zfsspec.implementations.memoryr  Zfsspec.registryr  r  r  storeclear)r  r  registryr  r'   r'   r(   
fsspectest^  s   

r  )r   NN)ZEgonZVenkmanN)NCC1701Dr  r  #tuple[Hashable, Hashable, Hashable]c                 C  r[   )zP
    A 3-tuple of names, the first two for operands, the last for a result.
    r\   r^   r'   r'   r(   r   t  s   r   c                 C  r[   )zI
    Parametrize over __setitem__, loc.__setitem__, iloc.__setitem__
    r\   r^   r'   r'   r(   indexer_sli  ra   r  c                 C  r[   )z<
    Parametrize over loc.__getitem__, iloc.__getitem__
    r\   r^   r'   r'   r(   
indexer_li  ra   r  c                 C  r[   )z8
    Parametrize over __setitem__, iloc.__setitem__
    r\   r^   r'   r'   r(   
indexer_si  ra   r  c                 C  r[   )z7
    Parametrize over __setitem__, loc.__setitem__
    r\   r^   r'   r'   r(   
indexer_sl  ra   r  c                 C  r[   )z:
    Parametrize over at.__setitem__, loc.__setitem__
    r\   r^   r'   r'   r(   
indexer_al  ra   r  c                 C  r[   )z<
    Parametrize over iat.__setitem__, iloc.__setitem__
    r\   r^   r'   r'   r(   indexer_ial  ra   r  boolc                   C  s   t jjjdkS )z>
    Fixture to check if the array manager is being used.
    r   )rL   optionsmodedata_managerr'   r'   r'   r(   using_array_manager  s   r  c                   C  s   t jjjot jjjdkS )z7
    Fixture to check if Copy-on-Write is enabled.
    block)rL   r  r  Zcopy_on_writer  r'   r'   r'   r(   using_copy_on_write  s   r  zEurope/Warsawzdateutil/Europe/Warsawc                 C  r[   )zE
    tzinfo for Europe/Warsaw using pytz, dateutil, or zoneinfo.
    r\   r^   r'   r'   r(   warsaw  ra   r  c                   C  s   dS )N)r^  rb  r'   r'   r'   r'   r(   arrow_string_storage  s   r  r   )r*   r+   r,   r-   r.   r-   r    r!   )r    r   )r    r   )r    r   )r    r
   )rC  r-   r    rJ  )r    r   )r    r  )r    r  )r    r-   (8  __doc__
__future__r   collectionsr   r   r   r   r   r   r  r	   operatorrL  pathlibr
   typingr   r   Zdateutil.tzr   r   Z
hypothesisr   stnumpyrK   r2   Zpytzr   r   Zpandas.util._test_decoratorsutilZ_test_decoratorstdZpandas.core.dtypes.dtypesr   r   ZpandasrL   r   r   r   r   r   r   Zpandas._testingZ_testingr   Zpandas.corer   Zpandas.core.indexes.apir   r   collections.abcr   r   r^  paImportErrorZhas_pyarrowZzoneinfoZZoneInfoZZoneInfoNotFoundErrorr)   r5   r?   settingsZregister_profileZHealthCheckZtoo_slowZload_profilesplitr/   r  Ztseriesr  clsZregister_type_strategyZbuildsZintegersZbooleansZfixturer;   rN   r`   Z
axis_framerb   rc   re   rf   ri   ro   rp   rq   r]   Z
skip_if_norw   ry   rz   r}   r   ZNULL_OBJECTSr   Znulls_fixture2r  ZNaTr   Zunique_nulls_fixture2ZNP_NAT_OBJECTSr   Znp_nat_fixture2r   r   Zindex_or_series2r   r   r   Zbox_with_array2r   r   r   r   r   r   r   ZmakeStringIndexZmakeDateIndexZmakePeriodIndexZmakeTimedeltaIndexZmakeRangeIndexZmakeIntIndexZmakeUIntIndexZmakeFloatIndexZmakeBoolIndexr   rh  r   r   r   ZmakeNumericIndexZmakeCategoricalIndexZmakeIntervalIndexr   rt   r  r  r   idxkeysrO   Zindex_fixture2r=   r   Zindex_flat2r   r   r   r   r  Z_seriesr  r	  ZNARROW_NP_DTYPESZ_narrow_seriesr  r  ZPYTHON_DATA_TYPESZ_typ_objects_seriesr  r  r  r  r  r  r  r#  Zarithmetic_dunder_methodsr%  addZraddsubZrsubmulZrmultruedivZrtruedivfloordivZ	rfloordivmodZrmodpowZrpoweqneltlegtgeand_Zrand_xorZrxoror_Zror_r&  r(  Z_all_numeric_reductionsr/  Z_all_boolean_reductionsr2  Z_all_reductionsr3  r4  r9  r@  Z_all_numeric_accumulationsrB  rC  rG  rI  rT  rV  Z	TIMEZONESextendZTIMEZONE_IDSZparametrize_fixture_docr-   rY  rZ  Ztz_aware_fixture2Z_UTCSappendr[  Zutc_fixture2ZSTRING_DTYPESr\  r_  rc  rd  Zstring_storage2ZBYTES_DTYPESre  ZOBJECT_DTYPESrg  ri  ZDATETIME64_DTYPESrj  ZTIMEDELTA64_DTYPESrk  rq  ZFLOAT_NUMPY_DTYPESrr  ZFLOAT_EA_DTYPESrs  ZALL_FLOAT_DTYPESrt  ZCOMPLEX_DTYPESru  ZSIGNED_INT_NUMPY_DTYPESrv  ZUNSIGNED_INT_NUMPY_DTYPESrw  ZALL_INT_NUMPY_DTYPESrx  ZALL_INT_EA_DTYPESry  ZALL_INT_DTYPESrz  r{  ZALL_INT_PYARROW_DTYPES_STR_REPRZFLOAT_PYARROW_DTYPES_STR_REPRr|  ZSIGNED_INT_EA_DTYPESr}  ZALL_REAL_NUMPY_DTYPESr~  ZALL_REAL_DTYPESr  ZALL_NUMPY_DTYPESr  ZALL_NUMERIC_DTYPESr  ZNAr  Z_any_skipna_inferred_dtyperZ   _r  r  r  __all__r  r  r  r   setitemlocr  r  r  r  r  atr  Ziatr  r  r  Zwarsawsr  r  r'   r'   r'   r(   <module>   sb    
A






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

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
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	

"

	
			



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

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