Skip to main content
`Ctrl`+`K`

# pandas.read_spss

pandas.read_spss(path, usecols=None, convert_categoricals=True, dtype_backend=<no_default>, **kwargs)

  Load an SPSS file from the file path, returning a DataFrame.

  This function reads data saved in the SPSS `.sav` format using the `pyreadstat` library, which must be installed separately.

  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 `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 `DataFrame`

      - `"pyarrow"`: returns pyarrow-backed nullable `ArrowDtype` `DataFrame`

      Added in version 2.0.

    **kwargs

      Additional keyword arguments that can be passed to `pyreadstat.read_sav()`.

      Added in version 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")