pandas.read_spss#
- pandas.read_spss(path, usecols=None, convert_categoricals=True, dtype_backend=<no_default>, **kwargs)[source]#
- Load an SPSS file from the file path, returning a DataFrame. - Parameters:
- pathstr or Path
- File path. 
- usecolslist-like, optional
- Return a subset of the columns. If None, return all columns. 
- convert_categoricalsbool, 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")