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- from pathlib import Path
- from typing import Optional, Sequence, Union
- from pandas.compat._optional import import_optional_dependency
- from pandas.core.dtypes.inference import is_list_like
- from pandas.core.api import DataFrame
- def read_spss(
- path: Union[str, Path],
- usecols: Optional[Sequence[str]] = None,
- convert_categoricals: bool = True,
- ) -> DataFrame:
- """
- Load an SPSS file from the file path, returning a DataFrame.
- .. versionadded:: 0.25.0
- Parameters
- ----------
- path : string 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.
- Returns
- -------
- DataFrame
- """
- pyreadstat = import_optional_dependency("pyreadstat")
- if usecols is not None:
- if not is_list_like(usecols):
- raise TypeError("usecols must be list-like.")
- else:
- usecols = list(usecols) # pyreadstat requires a list
- df, _ = pyreadstat.read_sav(
- path, usecols=usecols, apply_value_formats=convert_categoricals
- )
- return df
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