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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

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