o d@sddlmZddlmZddlmZmZddlmZddl m Z ddl m Z ddl mZddlmZer@dd lmZdd lmZd d ejfdddZd S)) annotations)Path) TYPE_CHECKINGSequence)lib)import_optional_dependency)check_dtype_backend) is_list_like)stringify_path) DtypeBackend) DataFrameNTpath str | PathusecolsSequence[str] | Noneconvert_categoricalsbool dtype_backendDtypeBackend | lib.NoDefaultreturnr cCsbtd}t||durt|stdt|}|jt|||d\}}|tjur/|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"}, defaults to NumPy backed DataFrames Which dtype_backend to use, e.g. whether a DataFrame should have NumPy arrays, nullable dtypes are used for all dtypes that have a nullable implementation when "numpy_nullable" is set, pyarrow is used for all dtypes if "pyarrow" is set. The dtype_backends are still experimential. .. versionadded:: 2.0 Returns ------- DataFrame pyreadstatNzusecols must be list-like.)rapply_value_formats)r) rrr TypeErrorlistread_savr r no_defaultconvert_dtypes)r rrrrdf_rS/var/www/html/visualizacion-main/env/lib/python3.10/site-packages/pandas/io/spss.py read_spsss   r!) r rrrrrrrrr ) __future__rpathlibrtypingrr pandas._libsrpandas.compat._optionalrpandas.util._validatorsrpandas.core.dtypes.inferencer pandas.io.commonr pandas._typingr pandasr rr!rrrr s