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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
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Pass in the observed keyword to groupby for [True, False]
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Fixture for each null type in pandas, each null type exactly once.
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Fixture to parametrize over Index and Series, made necessary by a mypy
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Fixture for tests on indexes, series and series with a narrow dtype
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[30 rows x 4 columns]
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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
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[30 rows x 4 columns]
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[30 rows x 4 columns]
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Path to the file, relative to ``pandas/tests/``
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path including ``pandas/tests``.
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ValueError
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Fixture for trying explicit timezones: {0}
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)r r r r r r �datetime_tz_utcj s r� r z dateutil/UTCc C s | j S )zQ
Fixture to provide variants of UTC timezone strings and tzinfo objects.
)r8 )r9 r r r � utc_fixturer s r� c C s | j S )zR
Parametrized fixture for string dtypes.
* str
* 'str'
* 'U'
)r8 )r9 r r r � string_dtype} s r� c C s | j S )zK
Parametrized fixture for bytes dtypes.
* bytes
* 'bytes'
)r8 )r9 r r r � bytes_dtype� s r� c C s | j S )zN
Parametrized fixture for object dtypes.
* object
* 'object'
)r8 )r9 r r r � object_dtype� s r� c C s | j S )z\
Parametrized fixture for datetime64 dtypes.
* 'datetime64[ns]'
* 'M8[ns]'
)r8 )r9 r r r �datetime64_dtype� s r� c C s | j S )z^
Parametrized fixture for timedelta64 dtypes.
* 'timedelta64[ns]'
* 'm8[ns]'
)r8 )r9 r r r �timedelta64_dtype� s r� c C s | j S )z^
Parameterized fixture for float dtypes.
* float
* 'float32'
* 'float64'
)r8 )r9 r r r � float_dtype� s r� c C s | j S )zg
Parameterized fixture for complex dtypes.
* complex
* 'complex64'
* 'complex128'
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complex_dtype� s r� c C s | j S )z|
Parameterized fixture for signed integer dtypes.
* int
* 'int8'
* 'int16'
* 'int32'
* 'int64'
)r8 )r9 r r r �
sint_dtype� s r� c C s | j S )zx
Parameterized fixture for unsigned integer dtypes.
* 'uint8'
* 'uint16'
* 'uint32'
* 'uint64'
)r8 )r9 r r r �
uint_dtype� s
r� c C s | j S )z�
Parameterized fixture for any integer dtype.
* int
* 'int8'
* 'uint8'
* 'int16'
* 'uint16'
* 'int32'
* 'uint32'
* 'int64'
* 'uint64'
)r8 )r9 r r r �
any_int_dtype� s r� c C s | j S )z�
Parameterized fixture for any nullable integer dtype.
* 'UInt8'
* 'Int8'
* 'UInt16'
* 'Int16'
* 'UInt32'
* 'Int32'
* 'UInt64'
* 'Int64'
)r8 )r9 r r r �any_nullable_int_dtype� s r� c C s | j S )z~
Parameterized fixture for any signed nullable integer dtype.
* 'Int8'
* 'Int16'
* 'Int32'
* 'Int64'
)r8 )r9 r r r � any_signed_nullable_int_dtype s
r� c C s | j S )z�
Parameterized fixture for any (purely) real numeric dtype.
* int
* 'int8'
* 'uint8'
* 'int16'
* 'uint16'
* 'int32'
* 'uint32'
* 'int64'
* 'uint64'
* float
* 'float32'
* 'float64'
)r8 )r9 r r r �any_real_dtype s r� c C s | j S )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'
)r8 )r9 r r r �any_numpy_dtype- s "r� r� r� �c�bytes� a� cr� z
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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
--------
>>> import pandas._libs.lib as 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
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Get an instance of IPython.InteractiveShell.
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Fixture for Tick based datetime offsets available for a time series.
)r8 )r9 r r r � tick_classes� s r c C s | S )Nr )r4 r r r r5 � s c C s | j S )zk
Simple fixture for testing keys in sorting methods.
Tests None (no key) and the identity key.
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