§
    ÚóÉj=  ã                  ó‚   — d dl mZ d dlmZ d dlmZ d dlmZ d dlm	Z	 d dl
mZ d dlmZ  G d„ d	ee         ¦  «        Zd
S )é    )Úannotations)ÚGeneric)Ú#GET_CATEGORIES_DEPRECATION_TEMPLATE)Úissue_deprecation_warning)ÚVersion)ÚString)ÚSeriesTc                  ó   — e Zd Zdd„Zd	d„ZdS )
ÚSeriesCatNamespaceÚseriesr	   ÚreturnÚNonec                ó   — || _         d S )N)Ú_narwhals_series)Úselfr   s     úv/home/lighthouse/badge-speaker-benchmark/.benchmark-venv-community/lib/python3.11/site-packages/narwhals/series_cat.pyÚ__init__zSeriesCatNamespace.__init__   s   € Ø &ˆÔÐÐó    c                ó’  — | j         j        t          j        t          j        hv r;| j                              | j         j        j                             ¦   «         ¦  «        S t          t          j        d¬¦  «        d¬¦  «         | j                              d¬¦  «                             ¦   «                              t          ¦  «        S )a—  Get unique categories from column.

        Warning:
            This is deprecated and it will be removed in a future version, as Polars
            removed its own `cat.get_categories`.
            To get the distinct values present in a Categorical column, use
            [`Series.unique`][narwhals.series.Series.unique].
            For the fixed category list of an Enum, use its `dtype.categories`.

            Until it is removed, it is implemented as
            `unique(maintain_order=True).drop_nulls().cast(String)`, so it returns only
            the values which are actually present, in order of appearance.

        Note:
            In `narwhals.stable.v1` and `narwhals.stable.v2` this stays available, and
            keeps dispatching to each backend's native implementation.

        Examples:
            >>> import pandas as pd
            >>> import narwhals.stable.v2 as nw
            >>> s_native = pd.Series(["apple", "mango", "mango"], dtype="category")
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.cat.get_categories().to_native()
            0    apple
            1    mango
            dtype: str
        ÚSeries)Úclsz2.26.0)Ú_versionT)Úmaintain_order)r   r   r   ÚV1ÚV2Ú_with_compliantÚ_compliant_seriesÚcatÚget_categoriesr   r   ÚformatÚuniqueÚ
drop_nullsÚcastr   )r   s    r   r   z!SeriesCatNamespace.get_categories   s´   € ð8 Ô Ô)­g¬j½'¼*Ð-EÐEÐEØÔ(×8Ò8ØÔ%Ô7Ô;×JÒJÑLÔLñô ð õ 	"Ý/Ô6¸8ÐDÑDÔDÈxð	
ñ 	
ô 	
ð 	
ð Ô$×+Ò+¸4Ð+Ñ@Ô@×KÒKÑMÔM×RÒRÕSYÑZÔZÐZr   N)r   r	   r   r   )r   r	   )Ú__name__Ú
__module__Ú__qualname__r   r   © r   r   r   r      sB   € € € € € ð'ð 'ð 'ð 'ð$[ð $[ð $[ð $[ð $[ð $[r   r   N)Ú
__future__r   Útypingr   Únarwhals._constantsr   Únarwhals._exceptionsr   Únarwhals._utilsr   Únarwhals.dtypesr   Únarwhals.typingr	   r   r'   r   r   ú<module>r/      sÆ   ðØ "Ð "Ð "Ð "Ð "Ð "à Ð Ð Ð Ð Ð à CÐ CÐ CÐ CÐ CÐ CØ :Ð :Ð :Ð :Ð :Ð :Ø #Ð #Ð #Ð #Ð #Ð #Ø "Ð "Ð "Ð "Ð "Ð "Ø #Ð #Ð #Ð #Ð #Ð #ð([ð ([ð ([ð ([ð ([˜ Ô)ñ ([ô ([ð ([ð ([ð ([r   