a 鴫j@sddlmZddlmZddlmZddlmZddlm Z ddl m Z ddl m Z erddlmZdd lmZdd lmZdd lmZd d ejfddddddddZd S)) annotations) TYPE_CHECKING)lib)import_optional_dependency)check_dtype_backend) is_list_like)stringify_path)Sequence)Path) DtypeBackend) DataFrameNTz str | PathzSequence[str] | NoneboolzDtypeBackend | lib.NoDefaultr )pathusecolsconvert_categoricals dtype_backendreturncCsjtd}t||dur0t|s(tdt|}|jt|||d\}}|j|_|t j urf|j |d}|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.)rZapply_value_formats)r) rrr TypeErrorlistZread_savr__dict__attrsr no_defaultZconvert_dtypes)rrrrrZdfmetadatarM/var/www/html/laksyashrimp/venv/lib/python3.9/site-packages/pandas/io/spss.py read_spsss$   r) __future__rtypingrZ pandas._libsrZpandas.compat._optionalrZpandas.util._validatorsrZpandas.core.dtypes.inferencerZpandas.io.commonrcollections.abcr pathlibr Zpandas._typingr Zpandasr rrrrrrs