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kwargs : dict
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Keyword arguments to pass to the functions.
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keys : list[Hashable] or Index
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Compute agg/apply results for dict-like input.
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selection : hashable or sequence of hashables
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s | j s|j |d¬« S |j |d¬« }|S # t t t f$ r |j |d¬« }Y |S w xY w)zõcompat apply method for funcs in listlikes and dictlikes.
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Used for each callable when giving listlikes and dictlikes of callables to
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apply. Needed for compatibility with Pandas < v2.1.
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.. versionadded:: 2.1.0
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rG c ó t rW rÝ rX s rE rY zResamplerWindowApply.apply_ rÞ rG c ó t rW rÝ rX s rE rr z ResamplerWindowApply.transformb rÞ rG )r@ rë rA r rú rû ) rò r r rB r rU rY rr r} r~ s @rE rê rê J s> ø
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ò""ö"rG rê c óö | du xr t di |¤}d}d}|sHt | t « r+t | « t t | « « kD r t d« | t d« |rt |« \ } }}| J || ||fS )aÆ
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This is the internal function to reconstruct func given if there is relabeling
|
or not and also normalize the keyword to get new order of columns.
|
|
If named aggregation is applied, `func` will be None, and kwargs contains the
|
column and aggregation function information to be parsed;
|
If named aggregation is not applied, `func` is either string (e.g. 'min') or
|
Callable, or list of them (e.g. ['min', np.max]), or the dictionary of column name
|
and str/Callable/list of them (e.g. {'A': 'min'}, or {'A': [np.min, lambda x: x]})
|
|
If relabeling is True, will return relabeling, reconstructed func, column
|
names, and the reconstructed order of columns.
|
If relabeling is False, the columns and order will be None.
|
|
Parameters
|
----------
|
func: agg function (e.g. 'min' or Callable) or list of agg functions
|
(e.g. ['min', np.max]) or dictionary (e.g. {'A': ['min', np.max]}).
|
**kwargs: dict, kwargs used in is_multi_agg_with_relabel and
|
normalize_keyword_aggregation function for relabelling
|
|
Returns
|
-------
|
relabelling: bool, if there is relabelling or not
|
func: normalized and mangled func
|
columns: tuple of column names
|
order: array of columns indices
|
|
Examples
|
--------
|
>>> reconstruct_func(None, **{"foo": ("col", "min")})
|
(True, defaultdict(<class 'list'>, {'col': ['min']}), ('foo',), array([0]))
|
|
>>> reconstruct_func("min")
|
(False, 'min', None, None)
|
NzFFunction names must be unique if there is no new column names assignedz4Must provide 'func' or tuples of '(column, aggfunc).rO )Úis_multi_agg_with_relabelrc rs r Úsetr rw Ú normalize_keyword_aggregation)rA r; Ú
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Ñ guð Ð ÐÐ à tW eÐ +Ð+rG c ób t d | j « D « « xr t | « dkD S )ax
|
Check whether kwargs passed to .agg look like multi-agg with relabeling.
|
|
Parameters
|
----------
|
**kwargs : dict
|
|
Returns
|
-------
|
bool
|
|
Examples
|
--------
|
>>> is_multi_agg_with_relabel(a="max")
|
False
|
>>> is_multi_agg_with_relabel(a_max=("a", "max"), a_min=("a", "min"))
|
True
|
>>> is_multi_agg_with_relabel()
|
False
|
c 3 ó\ K | ]$ }t |t « xr t |« d k( & yw)r N)rc ré r )rà r} s rE rá z,is_multi_agg_with_relabel.<locals>.<genexpr>À s' è ø ÒM¸z!UÓ#Ò3¬¨A«°!© Ó3ÑMùs *,r )r¿ r6 r )r; s rE rð rð « s- ô* ÑM¸V¿]¹]»_ÔMÓ Mò Ü F aðrG c
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« } || « j |« } ||| fS c c}} }w )aR
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Normalize user-provided "named aggregation" kwargs.
|
Transforms from the new ``Mapping[str, NamedAgg]`` style kwargs
|
to the old Dict[str, List[scalar]]].
|
|
Parameters
|
----------
|
kwargs : dict
|
|
Returns
|
-------
|
aggspec : dict
|
The transformed kwargs.
|
columns : tuple[str, ...]
|
The user-provided keys.
|
col_idx_order : List[int]
|
List of columns indices.
|
|
Examples
|
--------
|
>>> normalize_keyword_aggregation({"output": ("input", "sum")})
|
(defaultdict(<class 'list'>, {'input': ['sum']}), ('output',), array([0]))
|
r r¾ ) Úpandas.core.indexes.baser- r rs r± r r ri rt Ú_make_unique_kwarg_listÚ get_indexer) r; r- Úaggspecrô r ÚpairsÚcolumnÚaggfuncÚuniquified_orderÚaggfuncsÚ aggspec_orderÚuniquified_aggspecÚ col_idx_orders rE rò rò Å s õ< /ô
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Uniquify aggfunc name of the pairs in the order list
|
|
Examples:
|
--------
|
>>> kwarg_list = [('a', '<lambda>'), ('a', '<lambda>'), ('b', '<lambda>')]
|
>>> _make_unique_kwarg_list(kwarg_list)
|
[('a', '<lambda>_0'), ('a', '<lambda>_1'), ('b', '<lambda>')]
|
r4 r rD N)r Úcount)Úseqra Úpairs rE rù rù si ô ! ~÷ á Atð :=¿¹À4» È1Ò9LaT!WIQs 2 Aw}}¨TÓ 2Ð 3Ð4Ñ5ÐRVÑVó ð ùó s AAc ój ddl m} t t ||« d ¬« D cg c] }|d }}i }d}t | t
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|
Internal function to reorder result if relabelling is True for
|
dataframe.agg, and return the reordered result in dict.
|
|
Parameters:
|
----------
|
result: Result from aggregation
|
func: Dict of (column name, funcs)
|
columns: New columns name for relabelling
|
order: New order for relabelling
|
|
Examples
|
--------
|
>>> from pandas.core.apply import relabel_result
|
>>> result = pd.DataFrame(
|
... {"A": [np.nan, 2, np.nan], "C": [6, np.nan, np.nan], "B": [np.nan, 4, 2.5]},
|
... index=["max", "mean", "min"]
|
... )
|
>>> funcs = {"A": ["max"], "C": ["max"], "B": ["mean", "min"]}
|
>>> columns = ("foo", "aab", "bar", "dat")
|
>>> order = [0, 1, 2, 3]
|
>>> result_in_dict = relabel_result(result, funcs, columns, order)
|
>>> pd.DataFrame(result_in_dict, index=columns)
|
A C B
|
foo 2.0 NaN NaN
|
aab NaN 6.0 NaN
|
bar NaN NaN 4.0
|
dat NaN NaN 2.5
|
r r¾ c ó | d S )Nr4 rO )Úts rE ú<lambda>z relabel_result.<locals>.<lambda>: s
|
ÀaÈÁd rG )r¶ r4 Frº )rø r- Úsortedr± rc r$ r r r Údropnard ri rt rz rú r Úreindex)r rA r rô r- r Úreordered_indexesÚreordered_result_in_dictÚidxÚ reorder_maskr~ ÚfunÚsrm r s rE Úrelabel_resultr sC õF /ô #¤3 w°Ó#6¹NÔ KöØQðÐð ð 8:Ð Ø
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|
¸1¼cÔ0B×%Ñ% aÔ(ÈÑIðCð ñ " !§'¡'N× 6Ñ 6°sÓ ;MØ}Ñ%Að $ C¨#´°C³©.Ð9Ø()¯ © °'À¨ Ó(FÐ Ñ%ØCHnðE" ðF $Ð#ùòUùò>s ¡ D+ .D0c óx ddl m} t |fi |¤\ }}}}|r |J |J t | |||« } |||¬« } | S )Nr )r, rI )r¦ r, r? r )r rA r; r, ró r rô Úresult_in_dicts rE rÛ rÛ f s[ Ý ä'7¸Ñ'GÀÑ'GÑ$Jguáð Ð"Ð"Ð"ØÐ Ð Ð ä'¨°°g¸uÓEÙ>°Ô9à MrG c óÄ t | « dk r| S d}g }| D ]F }t j |« dk( rt |« }d| d|_ |dz }|j |« H |S )aJ
|
Possibly mangle a list of aggfuncs.
|
|
Parameters
|
----------
|
aggfuncs : Sequence
|
|
Returns
|
-------
|
mangled: list-like
|
A new AggSpec sequence, where lambdas have been converted
|
to have unique names.
|
|
Notes
|
-----
|
If just one aggfunc is passed, the name will not be mangled.
|
r4 r z<lambda>z<lambda_ú>)r ri rt r rò r )r ra Úmangled_aggfuncsrþ s rE Ú_managle_lambda_listr s{ ô$ 8}ÒàØ AØÐØò )Ü × Ñ Ó )¨ZÒ 7Ü gÓ&GØ!)¨!¨¨AGÔ Ø FAØ× Ñ Õ(ð )ð ÐrG c óú t | « }|s t | « s| S t | « « }|rC| j « D ]. \ }}t |« rt |« s t |« }n|}|||< 0 |S t | « }|S )aZ
|
Make new lambdas with unique names.
|
|
Parameters
|
----------
|
agg_spec : Any
|
An argument to GroupBy.agg.
|
Non-dict-like `agg_spec` are pass through as is.
|
For dict-like `agg_spec` a new spec is returned
|
with name-mangled lambdas.
|
|
Returns
|
-------
|
mangled : Any
|
Same type as the input.
|
|
Examples
|
--------
|
>>> maybe_mangle_lambdas('sum')
|
'sum'
|
>>> maybe_mangle_lambdas([lambda: 1, lambda: 2]) # doctest: +SKIP
|
[<function __main__.<lambda_0>,
|
<function pandas...._make_lambda.<locals>.f(*args, **kwargs)>]
|
)r r rñ r r )Úagg_specÚis_dictÚmangled_aggspecr¶ r r s rE Úmaybe_mangle_lambdasr ¢ s ô2 8Ó$GÙ | HÔ-ØØ$d8nÓ&OáØ %^^Ó -ò 4MCÜHÔ%¬l¸8Ô.DÜ#7¸Ó#AÑ à#+Ð à#3OCÒ ð 4ð Ðô /¨xÓ8à ÐrG c ó" d}t | « }g }| j « D ][ }t |t « s8t |« s-t |j t |« j « « |j |« ] |s d}t |« ||fS )aÜ
|
Validates types of user-provided "named aggregation" kwargs.
|
`TypeError` is raised if aggfunc is not `str` or callable.
|
|
Parameters
|
----------
|
kwargs : dict
|
|
Returns
|
-------
|
columns : List[str]
|
List of user-provided keys.
|
func : List[Union[str, callable[...,Any]]]
|
List of user-provided aggfuncs
|
|
Examples
|
--------
|
>>> validate_func_kwargs({'one': 'min', 'two': 'max'})
|
(['one', 'two'], ['min', 'max'])
|
z-func is expected but received {} in **kwargs.z2Must provide 'func' or named aggregation **kwargs.)
|
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ð !ð %ð !ð ð!ð *ð!ð ó!ôHL &ckkõ L &ô^:5ô :ôzi# ô i#ôX bJô bôJAzô AôHR,ô Rôj[5ô [ô|"<ô "ð8B,Ø
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ðB,àRóB,óJð4:+Ø ð:+ðó:+ðzØ "ðà óð$O$Ø ðO$à
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)ðO$ð ðO$ð ð O$ð
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ó O$ódó6 óB)ðX!Ø ð!à5ó!óHð Ø ðà
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ðð ðð
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ô rG
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