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    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'}
        Back-end data type applied to the resultant :class:`DataFrame`
        (still experimental). If not specified, the default behavior
        is to not use nullable data types. If specified, the behavior
        is as follows:

        * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
        * ``"pyarrow"``: returns pyarrow-backed
          nullable :class:`ArrowDtype` :class:`DataFrame`

        .. versionadded:: 2.0
    **kwargs
        Additional keyword arguments that can be passed to :func:`pyreadstat.read_sav`.

        .. versionadded:: 3.0

    Returns
    -------
    DataFrame
        DataFrame based on the SPSS file.

    See Also
    --------
    read_csv : Read a comma-separated values (csv) file into a pandas DataFrame.
    read_excel : Read an Excel file into a pandas DataFrame.
    read_sas : Read an SAS file into a pandas DataFrame.
    read_orc : Load an ORC object into a pandas DataFrame.
    read_feather : Load a feather-format object into a pandas DataFrame.

    Examples
    --------
    >>> df = pd.read_spss("spss_data.sav")  # doctest: +SKIP
    Ú
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