Ë
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ejN e(e(d iZ)d e*d < dddZ+dddZ,d dZ-d dZ.d dZ/d dZ0d dZ1d dZ2d d d!dZ3 d d"dZ4y)#é )Ú annotationsN)ÚAny)Úusing_string_dtype)Úimport_optional_dependency)ÚSettingWithCopyError)ÚBufferÚColumnÚColumnNullTypeÚ DataFrameÚ DtypeKind)Ú ArrowCTypesÚ
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_NP_DTYPESc ó t | t j « r| S t | d« r1 t dd¬« } |j | « j | ¬« S t | d« s t d« t | j |¬ « |¬ « S # |j $ r}t |« |d}~ww xY w# t $ r Y bw xY w)
|
aH
|
Build a ``pd.DataFrame`` from any DataFrame supporting the interchange protocol.
|
|
.. note::
|
|
For new development, we highly recommend using the Arrow C Data Interface
|
alongside the Arrow PyCapsule Interface instead of the interchange protocol.
|
From pandas 2.3 onwards, `from_dataframe` uses the PyCapsule Interface,
|
only falling back to the interchange protocol if that fails.
|
|
.. warning::
|
|
Due to severe implementation issues, we recommend only considering using the
|
interchange protocol in the following cases:
|
|
- converting to pandas: for pandas >= 2.0.3
|
- converting from pandas: for pandas >= 3.0.0
|
|
Parameters
|
----------
|
df : DataFrameXchg
|
Object supporting the interchange protocol, i.e. `__dataframe__` method.
|
allow_copy : bool, default: True
|
Whether to allow copying the memory to perform the conversion
|
(if false then zero-copy approach is requested).
|
|
Returns
|
-------
|
pd.DataFrame
|
|
Examples
|
--------
|
>>> df_not_necessarily_pandas = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
|
>>> interchange_object = df_not_necessarily_pandas.__dataframe__()
|
>>> interchange_object.column_names()
|
Index(['A', 'B'], dtype='object')
|
>>> df_pandas = (pd.api.interchange.from_dataframe
|
... (interchange_object.select_columns_by_name(['A'])))
|
>>> df_pandas
|
A
|
0 1
|
1 2
|
|
These methods (``column_names``, ``select_columns_by_name``) should work
|
for any dataframe library which implements the interchange protocol.
|
Ú__arrow_c_stream__Úpyarrowz14.0.0)Ú min_version)Úzero_copy_onlyNÚ __dataframe__z#`df` does not support __dataframe__)Ú
|
allow_copy) Ú
|
isinstanceÚpdr Úhasattrr ÚtableÚ to_pandasÚ ArrowInvalidÚ RuntimeErrorÚ ImportErrorÚ
|
ValueErrorÚ_from_dataframer )Údfr ÚpaÚes úYH:\Change_password\venv_build\Lib\site-packages\pandas/core/interchange/from_dataframe.pyÚfrom_dataframer* # sÄ ô^ "bllÔ#Ø ärÐ'Ô(ð -Ü+¨IÀ8ÔLBð
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-Øxx |×-Ñ-À¸^Ð-ÓLÐLô 2Ô 'ÜÐ>Ó?Ð?ä Ø
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×Ñ JÐÓ/¸Jô ð øð ??ò -Ü" 1o¨1Ð,ûð -ûô ò á ð ús( ª B1 ¸!B ÂB. B)Â)B.Â1 B=Â<B=c ób g }| j « D ] }t |« }|j |« |st |« dkD r t d« |s t | « }n-t |« dk( r|d }nt j |ddd¬« }| j j dd« }|||_ |S ) a
|
Build a ``pd.DataFrame`` from the DataFrame interchange object.
|
|
Parameters
|
----------
|
df : DataFrameXchg
|
Object supporting the interchange protocol, i.e. `__dataframe__` method.
|
allow_copy : bool, default: True
|
Whether to allow copying the memory to perform the conversion
|
(if false then zero-copy approach is requested).
|
|
Returns
|
-------
|
pd.DataFrame
|
r zHTo join chunks a copy is required which is forbidden by allow_copy=Falser TF)ÚaxisÚ ignore_indexÚcopyz pandas.indexN)
|
Ú
|
get_chunksÚprotocol_df_chunk_to_pandasÚappendÚlenr" r ÚconcatÚmetadataÚgetÚindex)r& r Ú
|
pandas_dfsÚchunkÚ pandas_dfÚ index_objs r) r% r% i sµ ð JØ ò %Ü/°Ó6 Ø×Ñ)Õ$ð%ñ #j/¨AÒ-ÜØ Vó
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ð
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ñ Ü/°Ó3 Ü Z AÒ Ø qM äIIj¨q¸tÈ%ÔP à °Ó5IØÐ Ø# à Ðó c óê i }g }| j « D ]6 }t |t « st d| d« ||v rt d| d« | j |« }|j
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d }|t j t j t j t j fv rt |« \ ||< }n~|t j k( rt |« \ ||< }nY|t j k( rt |« \ ||< }n4|t j k( rt# |« \ ||< }nt% d| d« |j' |« 9 t) j* |« }||j, d< |S )z¡
|
Convert interchange protocol chunk to ``pd.DataFrame``.
|
|
Parameters
|
----------
|
df : DataFrameXchg
|
|
Returns
|
-------
|
pd.DataFrame
|
zColumn z is not a stringz is not uniquer z
|
Data type z not handled yetÚ _INTERCHANGE_PROTOCOL_BUFFERS)Ú column_namesr Ústrr$ Úget_column_by_nameÚdtyper ÚINTÚUINTÚFLOATÚBOOLÚprimitive_column_to_ndarrayÚ CATEGORICALÚ categorical_column_to_seriesÚSTRINGÚstring_column_to_ndarrayÚDATETIMEÚdatetime_column_to_ndarrayÚNotImplementedErrorr1 r r Úattrs)r& ÚcolumnsÚbuffersÚnameÚcolrA Úbufr9 s r) r0 r0 sb ð !GØGØÓ!ó Ü$¤Ô$Ü w t fÐ,<Ð =Ó>Ð >Ø 7?Ü w t f¨NÐ ;Ó<Ð <Ø×#Ñ# DÓ)Ø ! Ø Ü MMÜ NNÜ OOÜ NNð
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ô "=¸SÓ!AÑ GDM3Ø i×+Ñ+Ò +Ü!=¸cÓ!BÑ GDM3Ø i×&Ñ&Ò &Ü!9¸#Ó!>Ñ GDM3Ø i×(Ñ(Ò (Ü!;¸CÓ!@Ñ GDM3ä%¨
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°5°'Ð9IÐ&JÓKÐ KàsÖð/ ô2 WÓ%IØ7>IOOÐ3Ñ4Ø Ðr; c ó¨ | j « }|d \ }}t ||| j | j « ¬« }t || |d « }||fS )aJ
|
Convert a column holding one of the primitive dtypes to a NumPy array.
|
|
A primitive type is one of: int, uint, float, bool.
|
|
Parameters
|
----------
|
col : Column
|
|
Returns
|
-------
|
tuple
|
Tuple of np.ndarray holding the data and the memory owner object
|
that keeps the memory alive.
|
Údata©ÚoffsetÚlengthÚvalidity)Ú get_buffersÚbuffer_to_ndarrayrW ÚsizeÚ set_nulls)rR rP Ú data_buffÚ
|
data_dtyperU s r) rF rF ¼ sZ ð ooÓ Gà # FOÑIzÜ Ø: c§j¡j¸¿¹»ô Dô T3 ¨
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|fS ) a
|
Convert a column holding categorical data to a pandas Series.
|
|
Parameters
|
----------
|
col : Column
|
|
Returns
|
-------
|
tuple
|
Tuple of pd.Series holding the data and the memory owner object
|
that keeps the memory alive.
|
Ú is_dictionaryz-Non-dictionary categoricals not supported yetÚ
|
categoriesÚ_colz}Interchanging categorical columns isn't supported yet, and our fallback of using the `col._col` attribute (a ndarray) failed.rU rV r Ú
|
is_ordered)rb ÚorderedrY )Údescribe_categoricalrM r ÚnpÚarrayrc rZ r[ rW r\ r2 r Ú CategoricalÚSeriesr] ) rR Ú categoricalÚ
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Convert a column holding string data to a NumPy array.
|
|
Parameters
|
----------
|
col : Column
|
|
Returns
|
-------
|
tuple
|
Tuple of np.ndarray holding the data and the memory owner object
|
that keeps the memory alive.
|
z3 null kind is not yet supported for string columns.Úoffsetsz#String buffers must contain offsetsrU é r r rV r NrY zutf-8)Úencodingr? ©rA Úobject) Ú describe_nullr
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Convert a column holding DateTime data to a NumPy array.
|
|
Parameters
|
----------
|
col : Column
|
|
Returns
|
-------
|
tuple
|
Tuple of np.ndarray holding the data and the memory owner object
|
that keeps the memory alive.
|
rU rB rV rY ) rZ rA r[ r rB Úgetattrr r r~ rW r\ r§ r] )rR rP r Ú col_bit_widthr¢ ÚdbufrU s r) rL rL s¤ ð ooÓ Gà&)§i¡iÑ#A}j !ØfoGD!ô Ø ä MMØ Ü K 3 } oÐ!6Ó 7Ü × Ñ ð
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t j |
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« S t j | j ||z dz z t j |« « } |d kD r"t j j! | |f¬
|
« S t j" g |¬ « S ) aÚ
|
Build a NumPy array from the passed buffer.
|
|
Parameters
|
----------
|
buffer : Buffer
|
Buffer to build a NumPy array from.
|
dtype : tuple
|
Data type of the buffer conforming protocol dtypes format.
|
offset : int, default: 0
|
Number of elements to offset from the start of the buffer.
|
length : int, optional
|
If the buffer is a bit-mask, specifies a number of bits to read
|
from the buffer. Has no effect otherwise.
|
|
Returns
|
-------
|
np.ndarray
|
|
Notes
|
-----
|
The returned array doesn't own the memory. The caller of this function is
|
responsible for keeping the memory owner object alive as long as
|
the returned NumPy array is being used.
|
NzConversion for ú is not yet supported.r z1`length` must be specified for a bit-mask buffer.r r¬ r r )Úshaperv )r r5 rM rg Ú ctypeslibÚas_ctypes_typer Ú BooleanArrayÚ from_buffersÚbool_Úforeign_bufferÚptrr ÚctypesÚcastÚPOINTERÚas_arrayrh ) ÚbufferrA rX rW ÚkindÚ bit_widthr Ú column_dtypeÚ ctypes_typer' ÚarrÚ data_pointers r) r[ r[ ° s: ð@ "ÑD)Qä >> $¨Ó+×/Ñ/° ¸4Ó@LØÐÜ! O°E°7Ð:PÐ"QÓRÐRô
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t j fv r>|sJ d« |\ }}t |||j |j « ¬« }|dk( r6| }n2|t j t j fv rnt d| d« |/t j |« r|s| j « } d| |< | S | S # t $ r | j# t$ « } d| |< Y | S t& $ r | j « } d| |< Y | S w xY w)aÆ
|
Set null values for the data according to the column null kind.
|
|
Parameters
|
----------
|
data : np.ndarray or pd.Series
|
Data to set nulls in.
|
col : Column
|
Column object that describes the `data`.
|
validity : tuple(Buffer, dtype) or None
|
The return value of ``col.buffers()``. We do not access the ``col.buffers()``
|
here to not take the ownership of the memory of buffer objects.
|
allow_modify_inplace : bool, default: True
|
Whether to modify the `data` inplace when zero-copy is possible (True) or always
|
modify a copy of the `data` (False).
|
|
Returns
|
-------
|
np.ndarray or pd.Series
|
Data with the nulls being set.
|
Nz/Expected to have a validity buffer for the maskrV r z
|
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|
Ú USE_SENTINELr rj rz r{ r[ rW r\ ry ÚUSE_NANrM rg Úanyr. Ú TypeErrorr Úfloatr ) rU rR rY Úallow_modify_inplacer
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|
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|
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|
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|
r rÌ r Ú pandas.core.interchange.utilsr r rB Úint8Úint16Úint32Úint64rC Úuint8Úuint16Úuint32r¡ rD Úfloat32Úfloat64rE rÉ r Ú__annotations__r* r% r0 rF rH rJ r§ rL r[ r] © r; r) ú<module>râ sB ðÞ "ã Û Ý ã å -å >Ý .ã ÷õ ÷ð MMrww B§H¡H°"·(±(ÀÇÁÑIØ NN b§i¡i°R·Y±YÀBÇIÁIÑNØ OO"**¨"¯*©*Ñ5Ø NN Ñ&ð /
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