o _~#g@sddlmZddlmZddlmZddlmZddlm Z ddl m Z ddl m Z erDddlmZdd lmZdd lmZdd lmZd d ejfdddZd 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 cCsjtd}t||durt|stdt|}|jt|||d\}}|j|_|t j ur3|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.)rapply_value_formats)r) rrr TypeErrorlistread_savr__dict__attrsr no_defaultconvert_dtypes)r rrrrdfmetadatar!s/var/www/static.ux5.de/https/Moving-Object-Detection-with-OpenCV/env/lib/python3.10/site-packages/pandas/io/spss.py read_spsss$    r#) r rrrrrrrrr ) __future__rtypingr pandas._libsrpandas.compat._optionalrpandas.util._validatorsrpandas.core.dtypes.inferencerpandas.io.commonrcollections.abcr pathlibr pandas._typingr pandasr rr#r!r!r!r"s