U md@sddlmZddlmZddlmZmZddlmZddl m Z ddl m Z ddl mZddlmZerdd lmZdd lmZd d ejfd dddddddZd S)) annotations)Path) TYPE_CHECKINGSequence)lib)import_optional_dependency)check_dtype_backend) is_list_like)stringify_path) DtypeBackend) DataFrameNTz str | PathzSequence[str] | NoneboolzDtypeBackend | lib.NoDefaultr )pathusecolsconvert_categoricals dtype_backendreturncCsbtd}t||dk r0t|s(tdt|}|jt|||d\}}|tjk r^|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.)rZapply_value_formats)r) rrr TypeErrorlistZread_savr r no_defaultZconvert_dtypes)rrrrrZdf_rG/home/sam/Atlas/atlas_env/lib/python3.8/site-packages/pandas/io/spss.py read_spsss   r) __future__rpathlibrtypingrrZ pandas._libsrZpandas.compat._optionalrZpandas.util._validatorsrZpandas.core.dtypes.inferencer Zpandas.io.commonr Zpandas._typingr Zpandasr rrrrrrs