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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
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Parameters
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item : pytest.Item
pytest test item.
path : str
Module path to Python object, e.g. "pandas.DataFrame.append". A
warning will be filtered when item.name ends with in given path. So it is
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message : str
Message to be filtered.
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Make `np` and `pd` names available for doctests.
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Configure settings for all tests and test modules.
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Fixture for returning the axis numbers of a DataFrame.
<20><01>param<61><01>requests r/<00>axisr<73><00><00><00>
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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<>s r/<00>observedr<64><00><00><00> <13>=<3D>=<3D>r1)TFNc<01><00>|jS)z6
Boolean 'ordered' parameter for Categorical.
r<>r<>s r/<00>orderedr<64>+r<>r1c<01><00>|jS)z%
Boolean 'dropna' parameter.
r<>r<>s r/<00>dropnar<61>3r<>r1c<01><00>|jS)z#
Boolean 'sort' parameter.
r<>r<>s r/<00>sortr<74>;r<>r1c<01><00>|jS)z%
Boolean 'skipna' parameter.
r<>r<>s r/<00>skipnar<61>Cr<>r1)<03>first<73>lastFc<01><00>|jS)z[
Valid values for the 'keep' parameter used in
.duplicated or .drop_duplicates
r<>r<>s r/<00>keepr<70>K<00><00><00> <13>=<3D>=<3D>r1)<04>both<74>neither<65>left<66>rightc<01><00>|jS)zA
Fixture for trying all interval 'inclusive' parameters.
r<>r<>s r/<00>inclusive_endpoints_fixturer<65>Tr<>r1)r<>r<>r<>r<>c<01><00>|jS)z<
Fixture for trying all interval closed parameters.
r<>r<>s r/<00>closedr<64>\r<>r1c<01><00>|jS)zS
Secondary closed fixture to allow parametrizing over all pairs of closed.
r<>r<>s r/<00> other_closedr<64>dr<>r1<00>gzip<69>bz2<7A>zip<69>xz<78>tar<61>zstd<74> zstandard)<01>marksc<01><00>|jS)zK
Fixture for trying common compression types in compression tests.
r<>r<>s r/<00> compressionr<6E>l<00><00><00> <13>=<3D>=<3D>r1c<01><00>|jS)zk
Fixture for trying common compression types in compression tests excluding
uncompressed case.
r<>r<>s r/<00>compression_onlyr<79>~r<>r1c<01><00>|jS)z,
Fixture that an array is writable.
r<>r<>s r/<00>writabler<65><00>r<>r1)<04>inner<65>outerr<72>r<>c<01><00>|jS)z:
Fixture for trying all types of join operations.
r<>r<>s r/<00> join_typer<65><00>r<>r1<00>nlargest<73> nsmallestc<01><00>|jS)z1
Fixture for trying all nselect methods.
r<>r<>s r/<00>nselect_methodr<64><00>r<>r1c<01><00>|jS)z2
Fixture for 'na_action' argument in map.
r<>r<>s r/<00> na_actionr<6E><00>r<>r1c<01><00>|jS)zJ
Fixture for 'na_action' argument in sort_values/sort_index/rank.
r<>r<>s r/<00> ascendingr<67><00>r<>r1)<05>average<67>min<69>maxr<78><00>densec<01><00>|jS)z.
Fixture for 'rank' argument in rank.
r<>r<>s r/<00> rank_methodr<64><00>r<>r1c<01><00>|jS)z5
Fixture for 'as_index' argument in groupby.
r<>r<>s r/<00>as_indexr<78><00>r<>r1c<01><00>|jS)z6
Fixture for 'cache' argument in to_datetime.
r<>r<>s r/<00>cacher<65><00>r<>r1c<01><00>|jS)z>
Fixture for parallel keyword argument for numba.jit.
r<>r<>s r/<00>parallelr<6C><00>r<>r1c<01><00>|jS)z;
Fixture for nogil keyword argument for numba.jit.
r<>r<>s r/<00>nogilr<6C><00>r<>r1c<01><00>|jS)z>
Fixture for nopython keyword argument for numba.jit.
r<>r<>s r/<00>nopythonr<6E><00>r<>r1c<01>,<00>t|<00>jS<00>N<><02>type<70>__name__r<5F>s r/r<>r<><00>s<00><00>d<EFBFBD>1<EFBFBD>g<EFBFBD>6F<36>6F<36>r1c<01><00>|jS)z/
Fixture for each null type in pandas.
r<>r<>s r/<00> nulls_fixturer<65><00>r<>r1c<01><00>|jS)zL
Fixture for each null type in pandas, each null type exactly once.
r<>r<>s r/<00>unique_nulls_fixturer<65><00>r<>r1c<01>,<00>t|<00>jSr<>r<>r<>s r/r<>r<>s<00><00><04>Q<EFBFBD><07>8H<38>8H<38>r1c<01><00>|jS)z-
Fixture for each NaT type in numpy.
r<>r<>s r/<00>np_nat_fixturer<65>r<>r1c<01><00>|jS)z;
Fixture to parametrize over DataFrame and Series.
r<>r<>s r/<00>frame_or_seriesr<73>r<>r1r<00>seriesc<01><00>|jS)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<>s r/<00>index_or_seriesr<73>r<>r1)rr<><00>arrayc<01><00>|jS)zG
Fixture to parametrize over Index, Series, and ExtensionArray
r<>r<>s r/<00>index_or_series_or_arrayr<79>,r<>r1c<01><00>|jSr<>)r<>r<>s r/r<>r<>4s
<00><00>1<EFBFBD>:<3A>:<3A>r1c<01><00>|jS)z]
Fixture to test behavior for Index, Series, DataFrame, and pandas Array
classes
r<>r<>s r/<00>box_with_arrayr<79>4r<>r1c<01>$<00>Gd<01>dt<00>}|S)z,
Fixture for a dictionary subclass.
c<01><00>eZdZdd<01>Zy)<04>"dict_subclass.<locals>.TestSubDictc<01>6<00>tj|g|<01><01>i|<02><01>yr<>)<02>dict<63>__init__)r7<00>args<67>kwargss r/r<>z+dict_subclass.<locals>.TestSubDict.__init__Gs<00><00> <10>M<EFBFBD>M<EFBFBD>$<24> 0<><14> 0<><16> 0r1N<><02>return<72>None)r<><00>
__module__r6r<>r}r1r/<00> TestSubDictr<74>Fs<00><00> 1r1r<>)r<>)r<>s r/<00> dict_subclassr<73>@s<00><00> 1<>d<EFBFBD>1<> <17>r1c<01>8<00>Gd<01>dtj<00>}|S)z8
Fixture for a non-mapping dictionary subclass.
c<01>*<00>eZdZdd<01>Zd<02>Zdd<03>Zdd<04>Zy) <09>5non_dict_mapping_subclass.<locals>.TestNonDictMappingc<01><00>||_yr<>)<01>_data)r7<00>underlying_dicts r/r<>z>non_dict_mapping_subclass.<locals>.TestNonDictMapping.__init__Ts <00><00>(<28>D<EFBFBD>Jr1c<01>8<00>|jj|<01>Sr<>)r<><00> __getitem__)r7<00>keys r/r<>zAnon_dict_mapping_subclass.<locals>.TestNonDictMapping.__getitem__Ws<00><00><17>:<3A>:<3A>)<29>)<29>#<23>.<2E> .r1c<01>6<00>|jj<00>Sr<>)r<><00>__iter__<5F>r7s r/rz>non_dict_mapping_subclass.<locals>.TestNonDictMapping.__iter__Zs<00><00><17>:<3A>:<3A>&<26>&<26>(<28> (r1c<01>6<00>|jj<00>Sr<>)r<><00>__len__rs r/rz=non_dict_mapping_subclass.<locals>.TestNonDictMapping.__len__]s<00><00><17>:<3A>:<3A>%<25>%<25>'<27> 'r1Nr<4E>)r<>r$)r<><00>int)r<>r<>r6r<>r<>rrr}r1r/<00>TestNonDictMappingr<67>Ss<00><00> )<29> /<2F> )<29> (r1r)r<00>Mapping)rs r/<00>non_dict_mapping_subclassr Ms<00><00> (<28>S<EFBFBD>[<5B>[<5B> (<28> <1E>r1c <01><><00>ttjjd<01>j d<02>t t d<03><00>tddd<06><07><00><08>}|jd <09>d
<EFBFBD>d <0B>g<03>j<00>}|jj|jjD<00>cgc]}|jd <0C><00><02>c}<02>|_
|jjgd <0A>d<0E><0F>|Scc}w)z<>
DataFrame with 3 level MultiIndex (year, month, day) covering
first 100 business days from 2000-01-01 with random data
<20>)<02>d<00><00>ABCD<43>
2000-01-01r <00>B<><02>periods<64>freq)r<>rc<01><00>|jSr<>)<01>yearr<72>s r/r<>zAmultiindex_year_month_day_dataframe_random_data.<locals>.<lambda>qs
<00><00><11><16><16>r1c<01><00>|jSr<>)rpr<>s r/r<>zAmultiindex_year_month_day_dataframe_random_data.<locals>.<lambda>qs
<00><00>1<EFBFBD>7<EFBFBD>7<EFBFBD>r1c<01><00>|jSr<>)<01>dayr<79>s r/r<>zAmultiindex_year_month_day_dataframe_random_data.<locals>.<lambda>qs
<00><00>a<EFBFBD>e<EFBFBD>e<EFBFBD>r1<00>i8)rrprT)<01>inplace)rru<00>random<6F> default_rng<6E>standard_normalr <00>listr<00>groupby<62>sumr<00>
set_levels<EFBFBD>levels<6C>astype<70> set_names)<03>tdf<64>ymd<6D>levs r/<00>/multiindex_year_month_day_dataframe_random_datar(fs<><00><00> <14>
<EFBFBD> <09> <09><1D><1D>a<EFBFBD> <20>0<>0<><18>:<3A><15>d<EFBFBD>6<EFBFBD>l<EFBFBD>#<23><18><1C>s<EFBFBD><13>=<3D> <06>C<EFBFBD>
<0E>+<2B>+<2B>'<27>):<3A>O<EFBFBD>L<>
M<EFBFBD>
Q<EFBFBD>
Q<EFBFBD>
S<EFBFBD>C<EFBFBD><13> <09> <09>$<24>$<24>#<23>)<29>)<29>BR<42>BR<42>%S<>3<EFBFBD>c<EFBFBD>j<EFBFBD>j<EFBFBD><14>&6<>%S<>T<>C<EFBFBD>I<EFBFBD><07>I<EFBFBD>I<EFBFBD><17><17>0<>$<24><17>?<3F> <0E>J<EFBFBD><4A>&Ts<00>+C0c<01>:<00>tgd<01>gd<02>ggd<03>gd<04>gddg<02><07>S)z;
2-level MultiIndex, lexsorted, with string names.
<20><04>foo<6F>bar<61>baz<61>qux<75><03>one<6E>two<77>three)
rrrrlrlr r <00>r3r3)
rrlr rrlrlr rrlr r<><00>second)r"<00>codes<65>names)r!r}r1r/<00>%lexsorted_two_level_string_multiindexr7xs+<00><00>
<16>,<2C>.E<>F<>-<2D>/M<>N<><16><08>!<21> <06>r1c<01><><00>|}ttjjd<01>j d<02>|t gd<03>d<04><05><00><06>S)z2DataFrame with 2 level MultiIndex with random datar )<02>
r3)<03>Ar<00>C<>exp<78>rC<00>rr<>)rrurrrr )r7rs r/<00> multiindex_dataframe_random_datar?<00>s@<00><00>
2<>E<EFBFBD> <14>
<EFBFBD> <09> <09><1D><1D>a<EFBFBD> <20>0<>0<><17>9<><13><15>o<EFBFBD>E<EFBFBD>2<> <06>r1c<01><><00>tgd<01><01>}tddg<02>}tjgd<04><01>}tjgd<05><01>}ddg}t||g||g|d<08> <09>S)
zJ
MultiIndex used to test the general functionality of this object
r*r0r1)rrrlr r3r3)rrlrrlrrlr<>r4F)r"r5r6<00>verify_integrity)r rur<>r!)<05>
major_axis<EFBFBD>
minor_axis<EFBFBD> major_codes<65> minor_codes<65> index_namess r/<00>_create_multiindexrG<00>sh<00><00> <17>3<>4<>J<EFBFBD><16><05>u<EFBFBD>~<7E>&<26>J<EFBFBD><14>(<28>(<28>-<2D>.<2E>K<EFBFBD><14>(<28>(<28>-<2D>.<2E>K<EFBFBD><1A>H<EFBFBD>%<25>K<EFBFBD> <15><1A>J<EFBFBD>'<27><1A>K<EFBFBD>(<28><19><1E>  <06>r1c <01>Z<00>tjddgddgtddd<07><08>ggd <09><01>
<EFBFBD>S) zB
MultiIndex with a level that is a tzaware DatetimeIndex.
rlr <00>a<>b<>20130101r3<00>
US/Eastern<72>r<00>tzr/)r6)r!<00> from_productrr}r1r/<00>_create_mi_with_dt64tz_levelrP<00>s5<00><00>
<16> "<22> "<22>
<0B>Q<EFBFBD><16>#<23>s<EFBFBD><1A>Z<EFBFBD>
<EFBFBD>A<EFBFBD>,<2C>O<>P<>%<25> <06>r1r9r9<00>pandas_<73><01>dtype<70>stringrz
2020-01-01)rz datetime-tzz
US/PacificrM<00>period<6F>Drrz1 day)<03>startrr<00>range<67>int8<74>int16<31>int32<33>int64<36>uint8<74>uint16<31>uint32<33>uint64<36>float32<33>float64z bool-object<63>
bool-dtype<70> complex64y<00>?<3F>
complex128<EFBFBD> categorical<61>abcdr <00>intervalr <00> )<01>num<75>empty<74>tuples)r+r,r-)rlr r3)<01>strict<63>mi-with-dt64tz-level<65>multi<74>repeats)rrrlrlr r <00> nullable_int<6E>Int64<36> nullable_uint<6E>UInt16<31>nullable_float<61>Float32<33> nullable_bool<6F>booleanz string-pythonzstring[python]zstring[pyarrow]zstring-pyarrowc<01>H<00>t|jjd<01><02>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
- ...
F<><01>deep)<03> indices_dictr<74><00>copyr<79>s r/rr<00>s!<00><00> <18><07> <0A> <0A> &<26> +<2B> +<2B><15> +<2B> 7<>7r1c<01>L<00>|j}t|jd<01><02>S)z8
index fixture, but excluding MultiIndex cases.
Frz)r<>r|r})r<>rs r/<00>
index_flatr<00>s&<00><00> <12>-<2D>-<2D>C<EFBFBD> <17><03> <1C> !<21> !<21>u<EFBFBD> !<21> -<2D>-r1)r<00>uint<6E>float)rXrkrprcc<01>8<00>t|j}|jdvrC|j<00>}dg|ddd<00><01>|d<dg|ddd<00><01>|d<tj|<02>S|j
j <00>}d|d<d|d<t|<01>|d<06><07>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.
)rlrnroNrrl<00><><EFBFBD><EFBFBD><EFBFBD>F)r})r|r<><00>tolistr!<00> from_tuples<65>valuesr}r<>)r<><00>ind<6E>valss r/<00>index_with_missingr<67><00>s<><00><00>( <17>w<EFBFBD>}<7D>}<7D>
%<25>C<EFBFBD><0E>}<7D>}<7D>C<>C<><12>z<EFBFBD>z<EFBFBD>|<7C><04><17>&<26>$<24>q<EFBFBD>'<27>!<21>"<22>+<2B>&<26><04>Q<EFBFBD><07><18>(<28>4<EFBFBD><02>8<EFBFBD>A<EFBFBD>B<EFBFBD><<3C>(<28><04>R<EFBFBD><08><19>%<25>%<25>d<EFBFBD>+<2B>+<2B><12>z<EFBFBD>z<EFBFBD><EFBFBD><EFBFBD> <20><04><16><04>Q<EFBFBD><07><17><04>R<EFBFBD><08><18>t<EFBFBD>C<EFBFBD>y<EFBFBD><14>E<EFBFBD>*<2A>*r1c
<01><><00>ttjdtj<00><02>dzt t d<01>D<00>cgc]}d|<00><00><02><02> c}<00>d<05><06>Scc}w)zC
Fixture for Series of floats with Index of unique strings
<20>rRg<><67><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>?<3F>i_r<5F><00>rrC)rru<00>arangerbr rX<00><01>is r/<00> string_seriesr<73>!sK<00><00>
<12>
<EFBFBD> <09> <09>"<22>B<EFBFBD>J<EFBFBD>J<EFBFBD>'<27>#<23>-<2D><13>u<EFBFBD>R<EFBFBD>y<EFBFBD>1<>!<21>r<EFBFBD>!<21><13>X<EFBFBD>1<>2<> <15> <06><06><>1s<00> Ac<01><><00>td<01>D<00>cgc]}d|<00><00><02><02> }}ttd<01>D<00>cgc]}d|<00><00><02><02> c}<00>}t||dt<00><05>Scc}wcc}w)zI
Fixture for Series of dtype object with Index of unique strings
r<><00>foo_<6F>bar_<72>objects<74>rrCrS)rXr rr9)r<><00>datars r/<00> object_seriesr<73>-sY<00><00>
!&<26>b<EFBFBD> <09> *<2A>1<EFBFBD>d<EFBFBD>1<EFBFBD>#<23>J<EFBFBD> *<2A>D<EFBFBD> *<2A> <11>u<EFBFBD>R<EFBFBD>y<EFBFBD>1<>!<21>T<EFBFBD>!<21><13>:<3A>1<> 2<>E<EFBFBD> <11>$<24>e<EFBFBD>)<29>6<EFBFBD> B<>B<><42> +<2B><>1s
<00> A<04> Ac<01><><00>ttjjd<01>j d<02>t ddd<04><05>d<06><07>S)z9
Fixture for Series of floats with DatetimeIndex
r r<>rrr<00>tsr<73>)rrurrrrr}r1r/<00>datetime_seriesr<73>7s=<00><00>
<12>
<EFBFBD> <09> <09><1D><1D>a<EFBFBD> <20>0<>0<><12>4<><18><1C>r<EFBFBD><03><<3C> <11> <06>r1c<01><><00>t|<00>}tjjd<01>j |<01>}t ||dd<03><04>S)zHelper for the _series dictr rIF)rrCr})<06>lenrurrrr)r<00>sizer<65>s r/<00>_create_seriesr<73>Cs;<00><00> <0E>u<EFBFBD>:<3A>D<EFBFBD> <0A>9<EFBFBD>9<EFBFBD> <20> <20><11> #<23> 3<> 3<>D<EFBFBD> 9<>D<EFBFBD> <11>$<24>e<EFBFBD>#<23>E<EFBFBD> :<3A>:r1z series-with-z-indexc<01><00>t|<00>S)zE
Fixture for tests on series with changing types of indices.
)r<><00>rs r/<00>series_with_simple_indexr<78>Ps<00><00>
<1A>%<25> <20> r1z-seriesr<73>zi-rIr<>c<01>H<00>t|jjd<01><02>S)z|
Fixture for tests on indexes, series and series with a narrow dtype
copy to avoid mutation, e.g. setting .name
Frz)<03>_index_or_series_objsr<73>r}r<>s r/<00>index_or_series_objr<6A>cs!<00><00> !<21><17><1D><1D> /<2F> 4<> 4<>%<25> 4<> @<40>@r1c<01>H<00>t|jjd<01><02>S)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
Frz)<03>_index_or_series_memory_objsr<73>r}r<>s r/<00>index_or_series_memory_objr<6A>ys!<00><00> (<28><07> <0A> <0A> 6<> ;<3B> ;<3B><15> ;<3B> G<>Gr1c
<01><><00>ttjdtj<00><02>t t d<03>D<00>cgc]}d|<00><00><02><02> c}<00>t t d<05><00><00><06>Scc}w)zj
Fixture for DataFrame of ints with index of unique strings
Columns are ['A', 'B', 'C', 'D']
<20>r<>r rRr<>r<>rr>)rru<00>onesr\r rXrr<>s r/<00> int_framer<65><00>sO<00><00> <15>
<EFBFBD><07><07><07>r<EFBFBD>x<EFBFBD>x<EFBFBD>(<28><13><15>r<EFBFBD><19>3<>A<EFBFBD>t<EFBFBD>A<EFBFBD>3<EFBFBD>Z<EFBFBD>3<>4<><15>d<EFBFBD>6<EFBFBD>l<EFBFBD>#<23> <06><06><>3s<00> A'c
<01><><00>ttjjd<01>j d<02>t t d<03>D<00>cgc]}d|<00><00><02><02> c}<00>t td<05><00><00><06>Scc}w)zm
Fixture for DataFrame of floats with index of unique strings
Columns are ['A', 'B', 'C', 'D'].
r r<>r<>r<>rr>)rrurrrr rXrr<>s r/<00> float_framer<65><00>sZ<00><00> <15>
<EFBFBD> <09> <09><1D><1D>a<EFBFBD> <20>0<>0<><17>9<><13><15>r<EFBFBD><19>3<>A<EFBFBD>t<EFBFBD>A<EFBFBD>3<EFBFBD>Z<EFBFBD>3<>4<><15>d<EFBFBD>6<EFBFBD>l<EFBFBD>#<23> <06><06><>3s<00> A0c<01>z<00>tddd<03>tddd<03>tddd<03>tddd<04>tddd<04>tddd<04>tddd<05>tddd<05>tddd<05>tddd<06>g
}ttjj d<03>j t |<00><00>|<00><07>S)zF
Fixture for Series with a DatetimeIndex that has duplicates.
i<>rlr r3r rkr<>)rrrurrrr<>)<01>datess r/<00>(rand_series_with_duplicate_datetimeindexr<78><00>s<><00><00> <11><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C><10><14>q<EFBFBD>!<21><1C> <06>E<EFBFBD> <12>"<22>)<29>)<29>'<27>'<27><01>*<2A>:<3A>:<3A>3<EFBFBD>u<EFBFBD>:<3A>F<>e<EFBFBD> T<>Tr1)r<>r<>r<>g<><67><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>?g<00>?z2012-01<30>M)rz period[M]z
2012-02-01z period[D]z
2011-01-01rL)rN<00>s)<02>unitrNi<>)<01>secondsztimedelta64[us]c<01><00>|jS)z;
Fixture that tests each scalar and datetime type.
r<>r<>s r/<00>ea_scalar_and_dtyper<65><00><00><00><00>" <13>=<3D>=<3D>r1c<01><00>|jS)zD
Fixture for dunder names for common arithmetic operations.
r<>r<>s r/<00>all_arithmetic_operatorsr<73><00>r<>r1c<01><00>|jS)zU
Fixture for operator and roperator arithmetic, comparison, and logical ops.
r<>r<>s r/<00>all_binary_operatorsr<73><00><00><00><00>D <13>=<3D>=<3D>r1c<01><00>|jS)z<>
Fixture for operator and roperator arithmetic functions.
Notes
-----
This includes divmod and rdivmod, whereas all_arithmetic_operators
does not.
r<>r<>s r/<00>all_arithmetic_functionsr<73>s<00><00>6 <13>=<3D>=<3D>r1) <0C>countr r<>r<><00>mean<61>prod<6F>std<74>var<61>median<61>kurt<72>skew<65>semc<01><00>|jS)z.
Fixture for numeric reduction names.
r<>r<>s r/<00>all_numeric_reductionsr<73>.r<>r1<00>all<6C>anyc<01><00>|jS)z.
Fixture for boolean reduction names.
r<>r<>s r/<00>all_boolean_reductionsr<73>9r<>r1c<01><00>|jS)z>
Fixture for all (boolean + numeric) reduction names.
r<>r<>s r/<00>all_reductionsr<73>Dr<>r1c<01><00>|jS)z;
Fixture for operator module comparison functions.
r<>r<>s r/<00> comparison_opr<70>L<00><00><00> <13>=<3D>=<3D>r1)<04>__le__<5F>__lt__<5F>__ge__<5F>__gt__c<01><00>|jS)zm
Fixture for dunder names for compare operations except == and !=
* >=
* >
* <
* <=
r<>r<>s r/<00>compare_operators_no_eq_ner<65>]r<>r1)<06>__and__<5F>__rand__<5F>__or__<5F>__ror__<5F>__xor__<5F>__rxor__c<01><00>|jS)zY
Fixture for dunder names for common logical operations
* |
* &
* ^
r<>r<>s r/<00>all_logical_operatorsr<73>j<00><00><00> <13>=<3D>=<3D>r1)<04>cumsum<75>cumprod<6F>cummin<69>cummaxc<01><00>|jS)z0
Fixture for numeric accumulation names
r<>r<>s r/<00>all_numeric_accumulationsr<73>{r<>r1c<01>$<00>|jd<01>S)zR
Returns the configuration for the test setting `--no-strict-data-files`.
r))r[)<01> pytestconfigs r/<00>strict_data_filesr<73><00>s<00><00>
<18> !<21> !<21>":<3A> ;<3B>;r1c<01><><00><00><02>tjjtjjt<00>d<01><00><02><02>fd<02>}|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.
<20>testsc<01><><00><02>tjj<00>g|<00><01><06>}tjj|<01>s*<2A>rt d|<01>d<02><03><00>t j d|<01>d<04><03>|S)NzCould not find file z' and --no-strict-data-files is not set.zCould not find r4)<07>osrJ<00>join<69>exists<74>
ValueErrorrF<00>skip)r<>rJ<00> BASE_PATHr<48>s <20><>r/<00>decozdatapath.<locals>.deco<63>sc<00><><00><11>w<EFBFBD>w<EFBFBD>|<7C>|<7C>I<EFBFBD>-<2D><04>-<2D><04><11>w<EFBFBD>w<EFBFBD>~<7E>~<7E>d<EFBFBD>#<23> <20> <20>*<2A>4<EFBFBD>&<26>0W<30>X<><12><12> <13>K<EFBFBD>K<EFBFBD>/<2F>$<24><16>q<EFBFBD>1<> 2<><13> r1)r<>rJr<><00>dirname<6D>__file__)r<>r<>r<>s` @r/<00>datapathr<68><00>s2<00><><00>&<13><07><07> <0C> <0C>R<EFBFBD>W<EFBFBD>W<EFBFBD>_<EFBFBD>_<EFBFBD>X<EFBFBD>6<><07>@<40>I<EFBFBD><14> <10>Kr1<00>UTCz
Asia/Tokyozdateutil/US/Pacificzdateutil/Asia/Singaporez+01:15z-02:15z UTC+01:15z UTC-02:15)<01>hoursr<73>r+r=i,i<><69><EFBFBD><EFBFBD>c<01><00>|jS)zD
Fixture for trying timezones including default (None): {0}
r<>r<>s r/<00>tz_naive_fixturer<65><00>r<>r1c<01><00>|jS)z4
Fixture for trying explicit timezones: {0}
r<>r<>s r/<00>tz_aware_fixturer<65><00>r<>r1<00>utcz dateutil/UTCc<01><00>|jS)zQ
Fixture to provide variants of UTC timezone strings and tzinfo objects.
r<>r<>s r/<00> utc_fixturer<00>r<>r1)r<><00>ms<6D>us<75>nsc<01><00>|jS)z&
datetime64 units we support.
r<>r<>s r/r<>r<><00>r<>r1c<01><00>|jS)zR
Parametrized fixture for string dtypes.
* str
* 'str'
* 'U'
r<>r<>s r/<00> string_dtyper<00><00><00> <13>=<3D>=<3D>r1<00>python<6F>pyarrow)<04>string=string[python]<5D>string=string[pyarrow]<5D>string=str[pyarrow]<5D>string=str[python]c<01>L<00>|j\}}tj||<02>S)z<>
Parametrized fixture for string dtypes.
* 'string[python]' (NA variant)
* 'string[pyarrow]' (NA variant)
* 'str' (NaN variant, with pyarrow)
* 'str' (NaN variant, without pyarrow)
)r<>rv<00> StringDtype<70>r<><00>storage<67>na_values r/<00>string_dtype_no_objectrs#<00><00>0 <20> <0A> <0A><15>G<EFBFBD>X<EFBFBD> <0A>><3E>><3E>'<27>8<EFBFBD> ,<2C>,r1c<01><00>|jS)za
Parametrized fixture for string dtypes.
* 'string[python]'
* 'string[pyarrow]'
r<>r<>s r/<00>nullable_string_dtyper*<00><00><00> <13>=<3D>=<3D>r1c<01>:<00>tj|j<00>S)zq
Parametrized fixture for string dtypes backed by Pyarrow.
* 'str[pyarrow]'
* 'string[pyarrow]'
)rvrr<>r<>s r/<00>pyarrow_string_dtyper:s<00><00> <0E>><3E>><3E>7<EFBFBD>=<3D>=<3D> )<29>)r1c<01><00>|jS<00>zb
Parametrized fixture for pd.options.mode.string_storage.
* 'python'
* 'pyarrow'
r<>r<>s r/<00>string_storagerJrr1c<01><00>|jS)z<>
Parametrized fixture for StringDtype storage and na_value.
* 'python' + pd.NA
* 'pyarrow' + pd.NA
* 'pyarrow' + np.nan
r<>r<>s r/<00>string_dtype_argumentsrZs<00><00>, <13>=<3D>=<3D>r1<00>numpy_nullablec<01><00>|jSrr<>r<>s r/<00> dtype_backendr!srr1c<01><00>|jS)zK
Parametrized fixture for bytes dtypes.
* bytes
* 'bytes'
r<>r<>s r/<00> bytes_dtyper#<00><00><00><00> <13>=<3D>=<3D>r1c<01><00>|jS)zN
Parametrized fixture for object dtypes.
* object
* 'object'
r<>r<>s r/<00> object_dtyper&<00>r$r1)z string=objectr r r rc<01><><00>t|jtj<00>r |jS|j\}}t j
||<02>S)z<>
Parametrized fixture for string dtypes.
* 'object'
* 'string[python]' (NA variant)
* 'string[pyarrow]' (NA variant)
* 'str' (NaN variant, with pyarrow)
* 'str' (NaN variant, without pyarrow)
)<06>
isinstancer<EFBFBD>rurSrvrrs r/<00>any_string_dtyper)<00>sA<00><00>2<12>'<27>-<2D>-<2D><12><18><18>*<2A><16>}<7D>}<7D><1C>$<24>M<EFBFBD>M<EFBFBD><19><07><18><11>~<7E>~<7E>g<EFBFBD>x<EFBFBD>0<>0r1c<01><00>|jS)z\
Parametrized fixture for datetime64 dtypes.
* 'datetime64[ns]'
* 'M8[ns]'
r<>r<>s r/<00>datetime64_dtyper+<00>r$r1c<01><00>|jS)z^
Parametrized fixture for timedelta64 dtypes.
* 'timedelta64[ns]'
* 'm8[ns]'
r<>r<>s r/<00>timedelta64_dtyper-<00>r$r1c <01>&<00>tddddddd<06><07>S)z-
Fixture emits fixed Timestamp.now()
i<>rlrmr <00> <00>)rrpr<00>hour<75>minuter4<00> microsecond)rr}r1r/<00> fixed_now_tsr4<00>s <00><00>
<15> <11><11><01><02>1<EFBFBD>R<EFBFBD>R<EFBFBD> <06>r1c<01><00>|jS)z^
Parameterized fixture for float dtypes.
* float
* 'float32'
* 'float64'
r<>r<>s r/<00>float_numpy_dtyper6<00>rr1c<01><00>|jS)zR
Parameterized fixture for float dtypes.
* 'Float32'
* 'Float64'
r<>r<>s r/<00>float_ea_dtyper8<00>r$r1c<01><00>|jS)z~
Parameterized fixture for float dtypes.
* float
* 'float32'
* 'float64'
* 'Float32'
* 'Float64'
r<>r<>s r/<00>any_float_dtyper:<00>r<>r1c<01><00>|jS)zg
Parameterized fixture for complex dtypes.
* complex
* 'complex64'
* 'complex128'
r<>r<>s r/<00> complex_dtyper<rr1c<01><00>|jS)z<>
Parameterized fixture for complex and numpy float dtypes.
* complex
* 'complex64'
* 'complex128'
* float
* 'float32'
* 'float64'
r<>r<>s r/<00>complex_or_float_dtyper>s<00><00> <13>=<3D>=<3D>r1c<01><00>|jS)z|
Parameterized fixture for signed integer dtypes.
* int
* 'int8'
* 'int16'
* 'int32'
* 'int64'
r<>r<>s r/<00>any_signed_int_numpy_dtyper@#r<>r1c<01><00>|jS)zx
Parameterized fixture for unsigned integer dtypes.
* 'uint8'
* 'uint16'
* 'uint32'
* 'uint64'
r<>r<>s r/<00>any_unsigned_int_numpy_dtyperB1r<>r1c<01><00>|jS)z<>
Parameterized fixture for any integer dtype.
* int
* 'int8'
* 'uint8'
* 'int16'
* 'uint16'
* 'int32'
* 'uint32'
* 'int64'
* 'uint64'
r<>r<>s r/<00>any_int_numpy_dtyperD>r<>r1c<01><00>|jS)z<>
Parameterized fixture for any nullable integer dtype.
* 'UInt8'
* 'Int8'
* 'UInt16'
* 'Int16'
* 'UInt32'
* 'Int32'
* 'UInt64'
* 'Int64'
r<>r<>s r/<00>any_int_ea_dtyperFPr<>r1c<01><00>|jS)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<>s r/<00> any_int_dtyperHas<00><00>. <13>=<3D>=<3D>r1c<01><00>|jS)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<>s r/<00>any_numeric_ea_dtyperJ{r<>r1c<01><00>|jS)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<>s r/<00>any_numeric_ea_and_arrow_dtyperL<00>s<00><00>@ <13>=<3D>=<3D>r1c<01><00>|jS)z~
Parameterized fixture for any signed nullable integer dtype.
* 'Int8'
* 'Int16'
* 'Int32'
* 'Int64'
r<>r<>s r/<00>any_signed_int_ea_dtyperN<00>r<>r1c<01><00>|jS)z<>
Parameterized fixture for any (purely) real numeric dtype.
* int
* 'int8'
* 'uint8'
* 'int16'
* 'uint16'
* 'int32'
* 'uint32'
* 'int64'
* 'uint64'
* float
* 'float32'
* 'float64'
r<>r<>s r/<00>any_real_numpy_dtyperP<00>s<00><00>$ <13>=<3D>=<3D>r1c<01><00>|jS)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<>s r/<00>any_real_numeric_dtyperR<00>s<00><00>( <13>=<3D>=<3D>r1c<01><00>|jS)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<>s r/<00>any_numpy_dtyperT<00>r<>r1c<01><00>|jS)a<>
Parameterized fixture for all real dtypes that can hold NA.
* float
* 'float32'
* 'float64'
* 'Float32'
* 'Float64'
* 'UInt8'
* 'UInt16'
* 'UInt32'
* 'UInt64'
* 'Int8'
* 'Int16'
* 'Int32'
* 'Int64'
* 'uint8[pyarrow]'
* 'uint16[pyarrow]'
* 'uint32[pyarrow]'
* 'uint64[pyarrow]'
* 'int8[pyarrow]'
* 'int16[pyarrow]'
* 'int32[pyarrow]'
* 'int64[pyarrow]'
* 'float[pyarrow]'
* 'double[pyarrow]'
r<>r<>s r/<00>any_real_nullable_dtyperVs<00><00>: <13>=<3D>=<3D>r1c<01><00>|jS)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<>s r/<00>any_numeric_dtyperX2s<00><00>> <13>=<3D>=<3D>r1<00>c<>mixed<65>bytes<65>a<>cz mixed-integerg@<40>floatingg<00>?<3F>integerzmixed-integer-float<61>decimal<61>
datetime64z
2013-01-01z
2018-01-01rK<00>20180101ri<>i<><00>complexy<00>?<00>?y@@rc<01>^<00>|j\}}tj|t<00><01>}||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
rR)r<>rur<>r9)r<><00>inferred_dtyper<65>s r/<00>any_skipna_inferred_dtyperfus0<00><00>R%<25>]<5D>]<5D><1A>N<EFBFBD>F<EFBFBD> <0F>X<EFBFBD>X<EFBFBD>f<EFBFBD>F<EFBFBD> +<2B>F<EFBFBD> <1A>6<EFBFBD> !<21>!r1c<01><><00>tjdd<02><03>ddlm}ddlm}|<01>}d|j _||<02><08>S) zj
Get an instance of IPython.InteractiveShell.
Will raise a skip if IPython is not installed.
<20>IPythonz6.0.0)<01>
minversionr)<01>InteractiveShell)<01>Configz:memory:)r])rF<00> importorskip<69>IPython.core.interactiveshellrj<00>traitlets.configrk<00>HistoryManager<65> hist_file)rjrkrYs r/<00>iprq<00>s<<00><00> <0B><17><17> <09>g<EFBFBD>6<>><3E>(<28><0E><08>A<EFBFBD>!+<2B>A<EFBFBD><14><14><1E> <1B>1<EFBFBD> %<25>%r1c#<01><>K<00>tjd<01>}tjd<02>}tjd<03>}|jj<00>} |j <00>5|j d<04>d<05><03>ddd<05>|jj <00>|jj|<03>|jd<06>tjd<07>y#1swY<00>exYw#|jj <00>|jj|<03>|jd<06>tjd<07>wxYw<01>w)a*
Ensure Matplotlib is cleaned up around a test.
Before a test is run:
1) Set the backend to "template" to avoid requiring a GUI.
After a test is run:
1) Reset units registry
2) Reset rc_context
3) Close all figures
See matplotlib/testing/decorators.py#L24.
<20>
matplotlibzmatplotlib.unitszmatplotlib.pyplot<6F>templateNr<4E>rl) rFrl<00>registryr}<00>
rc_context<EFBFBD>use<73>clear<61>update<74>close<73>gc<67>collect)<04>mpl<70> mpl_units<74>plt<6C>orig_units_registrys r/<00> mpl_cleanupr<70><00>s<00><00><><00>" <11>
<1D>
<1D>l<EFBFBD>
+<2B>C<EFBFBD><16>#<23>#<23>$6<>7<>I<EFBFBD>
<10>
<1D>
<1D>1<>
2<EFBFBD>C<EFBFBD>#<23>,<2C>,<2C>1<>1<>3<><17> <16> <10>^<5E>^<5E> <1D> <12> <0F>G<EFBFBD>G<EFBFBD>J<EFBFBD> <1F> <11> <12> <12><1A><1A> <20> <20>"<22><11><1A><1A>!<21>!<21>"5<>6<> <0B> <09> <09>%<25><18>
<EFBFBD>
<EFBFBD>
<EFBFBD>1<EFBFBD> <0A> <12> <12><> <12><1A><1A> <20> <20>"<22><11><1A><1A>!<21>!<21>"5<>6<> <0B> <09> <09>%<25><18>
<EFBFBD>
<EFBFBD>
<EFBFBD>1<EFBFBD> <0A>s8<00>AE<01>C3<00>-C'<03>C3<00> AE<01>'C0<07>,C3<00>3AE<03>E<01>Tickc<01><00>|jS)zN
Fixture for Tick based datetime offsets available for a time series.
r<>r<>s r/<00> tick_classesr<73><00>r<>r1c<01><00>|Sr<>r}r<>s r/r<>r<><00>s<00><00><01>r1c<01><00>|jS)zk
Simple fixture for testing keys in sorting methods.
Tests None (no key) and the identity key.
r<>r<>s r/<00> sort_by_keyr<79><00>r<>r1)r+NN)<03>Egon<6F>VenkmanN)<03>NCC1701Dr<44>r<>c<01><00>|jS)zP
A 3-tuple of names, the first two for operands, the last for a result.
r<>r<>s r/r6r6<00>s<00><00> <13>=<3D>=<3D>r1c<01><00>|jS)zI
Parametrize over __setitem__, loc.__setitem__, iloc.__setitem__
r<>r<>s r/<00> indexer_slir<69>r<>r1c<01><00>|jS)z<
Parametrize over loc.__getitem__, iloc.__getitem__
r<>r<>s r/<00>
indexer_lir<EFBFBD>r<>r1c<01><00>|jS)z8
Parametrize over __setitem__, iloc.__setitem__
r<>r<>s r/<00>
indexer_sir<EFBFBD>r<>r1c<01><00>|jS)z7
Parametrize over __setitem__, loc.__setitem__
r<>r<>s r/<00>
indexer_slr<EFBFBD>r<>r1c<01><00>|jS)z:
Parametrize over at.__setitem__, loc.__setitem__
r<>r<>s r/<00>
indexer_alr<EFBFBD>&r<>r1c<01><00>|jS)z<
Parametrize over iat.__setitem__, iloc.__setitem__
r<>r<>s r/<00> indexer_ialr<6C>.r<>r1c#<01><>K<00>tjd|j<00>5|jrtjjnd<02><02>ddd<03>y#1swYyxYw<01>w)z<>
Fixture to check if performance warnings are enabled. Either produces
``PerformanceWarning`` if they are enabled, otherwise ``False``.
zmode.performance_warningsFN)rv<00>option_contextr<74>r'<00>PerformanceWarningr<67>s r/<00>performance_warningr<67>6sM<00><00><><00>
<0C> <1A> <1A>6<><07> <0A> <0A> F<>G<01>.5<EFBFBD>m<EFBFBD>m<EFBFBD>b<EFBFBD>i<EFBFBD>i<EFBFBD>*<2A>*<2A><15>F<>G<01>G<01>G<01>s<00>!A#<01>+A<03> A#<01>A <07>A#c<01>N<00>tjjjduS)z=
Fixture to check if infer string option is enabled.
T)rv<00>options<6E>future<72> infer_stringr}r1r/<00>using_infer_stringr<67>@s<00><00>
<0E>:<3A>:<3A> <1C> <1C> )<29> )<29>T<EFBFBD> 1<>1r1c<01>N<00>tjjjduS)NT)rvr<>r<><00>python_scalarsr}r1r/<00>using_python_scalarsr<73>Hs<00><00> <0A>:<3A>:<3A> <1C> <1C> +<2B> +<2B>t<EFBFBD> 3<>3r1z Europe/Warsawzdateutil/Europe/Warsawz list[Any]<5D>_warsawsc<01><00>|jS)zE
tzinfo for Europe/Warsaw using pytz, dateutil, or zoneinfo.
r<>r<>s r/<00>warsawr<77>Rr<>r1c<01>f<00>|ttj<00><00>z }|j<00>|S)z<>
Generate a unique file for testing use. See link for removal policy.
https://docs.pytest.org/en/7.1.x/how-to/tmp_path.html#the-default-base-temporary-directory
)rA<00>uuid<69>uuid4<64>touch)<02>tmp_path<74> file_paths r/<00> temp_filer<65>Zs)<00><00> <19>3<EFBFBD>t<EFBFBD>z<EFBFBD>z<EFBFBD>|<7C>,<2C>,<2C>I<EFBFBD> <0A>O<EFBFBD>O<EFBFBD><15> <14>r1r?)<01>scopec#<01>zK<00>tjj<00>5}|<00><02>ddd<00>y#1swYyxYw<01>wr<>)rF<00> MonkeyPatch<63>context)<01>mps r/<00> monkeysessionr<6E>es3<00><00><><00> <0F> <1B> <1B> #<23> #<23> %<25><11><12><10><08><11><11><11>s<00>;<01>/<03> ;<01>8<07>;c#<01><>K<00>|j}tjd| <00>5|<01><02>ddd<00>y#1swYyxYw<01>w)Nzfuture.distinguish_nan_and_na)r<>rvr<>)r<><00>opts r/<00>using_nan_is_nar<61>ks;<00><00><><00>
<11>-<2D>-<2D>C<EFBFBD> <0B> <1A> <1A>:<3A><03>G<EFBFBD> D<><12><11> <09><12><12><12>s<00>$A<01>4<03> A<01>=<07>Ar<>)rIz pytest.ItemrJrArKrAr<>r<>)r<>z
type[dict])r<>ztype[abc.Mapping])r<>r!)r<>r)r<>r)r<>rAr<>zCallable[..., str])r<>r)r<>z#tuple[Hashable, Hashable, Hashable])r<>zIterator[bool | type[Warning]])r<><00>bool)r<>rA(H<00>__doc__<5F>
__future__r<00> collectionsrrrrrr r`r
r{<00>operatorr<72><00>typingr r r<><00> dateutil.tzr r<00>
hypothesisr<00>st<73>numpyrurF<00>pandas.compat._optionalr<00>pandas.util._test_decorators<72>util<69>_test_decorators<72>td<74>pandas.core.dtypes.dtypesrr<00>pandasrvrrrrrrrrrrrr<00>pandas._testing<6E>_testing<6E>tm<74> pandas.corer<00>pandas.core.indexes.apir r!<00>collections.abcr"r#r$r
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