cMhddlmZddlmZddlmZddlmZddlm Z ddl m Z ddl m Z erddlmZdd lmZdd lmZdd lmZd d ejfddZd S)) annotations) TYPE_CHECKING)lib)import_optional_dependency)check_dtype_backend) is_list_like)stringify_path)Sequence)Path) DtypeBackend) DataFrameNTpath str | PathusecolsSequence[str] | Noneconvert_categoricalsbool dtype_backendDtypeBackend | lib.NoDefaultreturnr cPtd}t||-t|stdt |}|t |||\}}|j|_|tj ur| |}|S)a Load an SPSS file from the file path, returning a DataFrame. Parameters ---------- path : str or Path File path. usecols : list-like, optional Return a subset of the columns. If None, return all columns. convert_categoricals : bool, default is True Convert categorical columns into pd.Categorical. dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable' Back-end data type applied to the resultant :class:`DataFrame` (still experimental). Behaviour is as follows: * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame` (default). * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype` DataFrame. .. versionadded:: 2.0 Returns ------- DataFrame Examples -------- >>> df = pd.read_spss("spss_data.sav") # doctest: +SKIP pyreadstatNzusecols must be list-like.)rapply_value_formats)r) rrr TypeErrorlistread_savr __dict__attrsr no_defaultconvert_dtypes)rrrrrdfmetadatas N/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/pandas/io/spss.py read_spssr$sH,L99J &&&G$$ :899 9w--&&tgCW'LB BHCN**   ]  ; ; I) rrrrrrrrrr ) __future__rtypingr pandas._libsrpandas.compat._optionalrpandas.util._validatorsrpandas.core.dtypes.inferencerpandas.io.commonr collections.abcr pathlibr pandas._typingr pandasr rr$r%r#r2s"""""" >>>>>>777777555555++++++!((((((++++++      %)!%25. 2222222r%