pandas.read_spss#
- pandas.read_spss(path, usecols=None, convert_categoricals=True, dtype_backend=<no_default>)[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’}, default ‘numpy_nullable’
Back-end data type applied to the resultant
DataFrame
(still experimental). Behaviour is as follows:"numpy_nullable"
: returns nullable-dtype-backedDataFrame
(default)."pyarrow"
: returns pyarrow-backed nullableArrowDtype
DataFrame.
Added in version 2.0.
- 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")