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-backedDataFrame"pyarrow": returns pyarrow-backed nullableArrowDtypeDataFrame
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_csvRead a comma-separated values (csv) file into a pandas DataFrame.
read_excelRead an Excel file into a pandas DataFrame.
read_sasRead an SAS file into a pandas DataFrame.
read_orcLoad an ORC object into a pandas DataFrame.
read_featherLoad a feather-format object into a pandas DataFrame.
Examples
>>> df = pd.read_spss("spss_data.sav")