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Jul 26, 2019
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DOC: add documentation for read_spss(#27476) #27594

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a2f714f
DOC: add documentation for read_spss (#27476)
another-green Jul 25, 2019
e600b04
DOC: add documentation for read_spss (#27476)
another-green Jul 26, 2019
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7 changes: 7 additions & 0 deletions doc/source/reference/io.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -105,6 +105,13 @@ SAS

read_sas

SPSS
~~~~
.. autosummary::
:toctree: api/

read_spss

SQL
~~~
.. autosummary::
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37 changes: 37 additions & 0 deletions doc/source/user_guide/io.rst
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Expand Up @@ -39,6 +39,7 @@ The pandas I/O API is a set of top level ``reader`` functions accessed like
binary;`Msgpack <https://msgpack.org/index.html>`__;:ref:`read_msgpack<io.msgpack>`;:ref:`to_msgpack<io.msgpack>`
binary;`Stata <https://en.wikipedia.org/wiki/Stata>`__;:ref:`read_stata<io.stata_reader>`;:ref:`to_stata<io.stata_writer>`
binary;`SAS <https://en.wikipedia.org/wiki/SAS_(software)>`__;:ref:`read_sas<io.sas_reader>`;
binary;`SPSS <https://en.wikipedia.org/wiki/SPSS>`__;:ref:`read_spss<io.spss_reader>`;
binary;`Python Pickle Format <https://docs.python.org/3/library/pickle.html>`__;:ref:`read_pickle<io.pickle>`;:ref:`to_pickle<io.pickle>`
SQL;`SQL <https://en.wikipedia.org/wiki/SQL>`__;:ref:`read_sql<io.sql>`;:ref:`to_sql<io.sql>`
SQL;`Google Big Query <https://en.wikipedia.org/wiki/BigQuery>`__;:ref:`read_gbq<io.bigquery>`;:ref:`to_gbq<io.bigquery>`
Expand Down Expand Up @@ -5477,6 +5478,42 @@ web site.

No official documentation is available for the SAS7BDAT format.

.. _io.spss:

.. _io.spss_reader:

SPSS formats
------------

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, 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 ``convert_categoricals=False``
to avoid converting categorical columns into ``pd.Categorical``.

Read a spss file:

.. code-block:: python

df = pd.read_spss('spss_data.zsav')

Extract a subset of columns ``usecols`` from SPSS file and
avoid converting categorical columns into ``pd.Categorical``:

.. code-block:: python

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.

.. _info: https://www.ibm.com/support/knowledgecenter/en/SSLVMB_22.0.0/com.ibm.spss.statistics.help/spss/base/savedatatypes.htm

.. _io.other:

Other file formats
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