DOC: add documentation for read_spss(pandas-dev#27476)

Author: another-green

doc/source/user_guide/io.rst

@@ -5489,10 +5489,11 @@ The top-level function :func:`read_spss` can read (but not write) SPSS
 `sav` (.sav) and  `zsav` (.zsav) format files(since *v0.25.0*).
 
 SPSS files contain column names. By default the
-whole file is read and returned as a ``DataFrame`` with all columns.
+whole file is read, categorical columns are converted into ``pd.Categorical``
+and a ``DataFrame`` with all columns is returned.
 
-Specify a ``usecols`` to obtain a subset of columns. Specify ``apply_value_formats=True``
-to convert categorical columns into ``pd.Categorical``.
+Specify a ``usecols`` to obtain a subset of columns. Specify ``convert_categoricals=False``
+to avoid converting categorical columns into ``pd.Categorical``.
 
 Read a spss file:
 
@@ -5501,11 +5502,11 @@ Read a spss file:
     df = pd.read_spss('spss_data.zsav')
 
 Extract a subset of columns ``usecols`` from SPSS file and
-convert categorical columns into ``pd.Categorical``:
+avoid converting categorical columns into ``pd.Categorical``:
 
 .. code-block:: python
 
-    df = pd.read_sas('spss_data.zsav', usecols=['foo', 'bar'], apply_value_formats=True)
+    df = pd.read_spss('spss_data.zsav', usecols=['foo', 'bar'], convert_categoricals=False)
 
 More info_ about the sav and zsav file format is available from the IBM
 web site.