g8 fddlmZddlZddlZddlmZddlmZddlmZddlmZddlm Z ddlm Z dd l m Z dd l m Z dd lmZdd lmZdd lmZddlmZddlmZddlmZddlmZerddlmZddlmZddlmZddlmZddddddddddd ZGd!d"Z d$d#Z!y)%) annotationsN)copy) TYPE_CHECKING)Any)Callable)Iterator)Sequence)is_simple_aggregation)parse_into_exprs)horizontal_concat)native_series_from_iterable)select_columns_by_name) set_columns)Implementation)find_stacklevel) remove_prefixPandasLikeDataFrame)PandasLikeSeries)IntoPandasLikeExpr) CompliantExprsummeanmedianmaxminstdvarsizenuniquecount) rrrrrrrlenn_uniquer!cHeZdZ ddZ ddZddZd dZy) PandasLikeGroupByc||_||_|jjtjur|jj dkr|st |jj|j|jj |jjjjjr d}t||jjjt|jddd|_ y|jjjt|jdd|d|_ y)N)r'z:Grouping by null values is not supported in pandas < 1.0.0FT)sortas_indexobserved)r(r)dropnar*)_df_keys_implementationrPANDAS_backend_versionr _native_frameisnaanyNotImplementedErrorgroupbylist_grouped)selfdfkeysdrop_null_keysmsgs S/var/www/openai/venv/lib/python3.12/site-packages/narwhals/_pandas_like/group_by.py__init__zPandasLikeGroupBy.__init__+s HH $ $(=(= =))F2#*HH**JJHH--HH,,  S)#.. HH22::TZZ  ;DM!HH22::TZZ % ;DMc t|d|jji|}|jj}t |j }|D]6}|j d}t||j|j 8t|j||j ||j|jjj||jj|jj S)N namespacezAnonymous expressions are not supported in group_by.agg. Instead of `nw.all()`, try using a named expression, such as `nw.col('a', 'b')` )dataframe_is_emptyimplementationbackend_versionnative_namespace)r r,__narwhals_namespace__r.rr- _output_names ValueErrorextend agg_pandasr7_from_native_framer1emptyr0__native_namespace__)r8aggs named_aggsexprsrC output_namesexprr<s r=aggzPandasLikeGroupBy.aggQs !  hh557   *.)A)A"&tzz"2 D!!)+ !o%    2 2 3 MM  JJ   # ##xx55;;) HH55!XX::<  r?cddlm}|||jj|jj|jj S)Nrr)rCrDversion)narwhals._pandas_like.dataframerr,r.r0_version)r8r9rs r=rKz$PandasLikeGroupBy._from_native_framess<G" 8833 HH55HH%%   r?c#Ktj5tjddt|jD]\}}||j |f dddy#1swYyxYww)Nignorez#.*a length 1 tuple will be returned)messagecategory)warningscatch_warningsfilterwarnings FutureWarningr7rK)r8keygroups r=__iter__zPandasLikeGroupBy.__iter__}s^  $ $ &  # #=&  #mm UD33E:;;, ' & &sA3AA' A3'A0,A3N)r9rr: list[str]r;boolreturnNone)rNrrOrrer)r9rrer)rez)Iterator[tuple[Any, PandasLikeDataFrame]])__name__ __module__ __qualname__r>rSrKrbr?r=r%r%*sT$%$-6$KO$ $L  !  )     D Fc ggfSNrjrjr?r=zagg_pandas..Rr?c ggfSrmrjrjr?r=rnzagg_pandas..ror?rz_Safety assertion failed, please report a bug to https://github.com/narwhals-dev/narwhals/issues_r'r rrddofz"Safety assertion failed, expected z got zH, please report a bug at https://github.com/narwhals-dev/narwhals/issues)r+)rr)columnsrCrDc3&K|] }|dkD ywr'Nrj).0vs r= zagg_pandas..)s@"?Q1q5"?sz - 'z' z timesz"Expected unique output names, got:)dfsrCrD)rs)inplaceauNo results for group-by aggregation. Hint: you were probably trying to apply a non-elementary aggregation with a pandas-like API. Please rewrite your query such that group-by aggregations are elementary. For example, instead of: df.group_by('a').agg(nw.col('b').round(2).mean()) use: df.with_columns(nw.col('b').round(2)).group_by('a').agg(nw.col('b').mean()) a5Found complex group-by expression, which can't be expressed efficiently with the pandas API. If you can, please rewrite your query such that group-by aggregations are simple (e.g. mean, std, min, max, ...). Please see: https://narwhals-dev.github.io/narwhals/pandas_like_concepts/improve_group_by_operation/) stacklevelcBg}g}D]}||}td|Dsd|jd}t||D]E}|j|jj d|j|j Gt||d S)Nc38K|]}t|dk(ywru)r")rvxs r=rxz+agg_pandas..func..^s9Lqs1v{Lsz Aggregation 'z' failed to aggregate - does your aggregation function return a scalar? 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