diff --git a/doc/source/io.rst b/doc/source/io.rst index e72224c6fa1fe..90167e7c6183f 100644 --- a/doc/source/io.rst +++ b/doc/source/io.rst @@ -29,36 +29,26 @@ IO Tools (Text, CSV, HDF5, ...) =============================== The pandas I/O API is a set of top level ``reader`` functions accessed like ``pd.read_csv()`` that generally return a ``pandas`` -object. - - * :ref:`read_csv` - * :ref:`read_excel` - * :ref:`read_hdf` - * :ref:`read_feather` - * :ref:`read_sql` - * :ref:`read_json` - * :ref:`read_msgpack` - * :ref:`read_html` - * :ref:`read_gbq` - * :ref:`read_stata` - * :ref:`read_sas` - * :ref:`read_clipboard` - * :ref:`read_pickle` - -The corresponding ``writer`` functions are object methods that are accessed like ``df.to_csv()`` - - * :ref:`to_csv` - * :ref:`to_excel` - * :ref:`to_hdf` - * :ref:`to_feather` - * :ref:`to_sql` - * :ref:`to_json` - * :ref:`to_msgpack` - * :ref:`to_html` - * :ref:`to_gbq` - * :ref:`to_stata` - * :ref:`to_clipboard` - * :ref:`to_pickle` +object. The corresponding ``writer`` functions are object methods that are accessed like ``df.to_csv()`` + +.. csv-table:: + :header: "Format Type", "Data Description", "Reader", "Writer" + :widths: 30, 100, 60, 60 + :delim: ; + + text;`CSV `__;:ref:`read_csv`;:ref:`to_csv` + text;`JSON `__;:ref:`read_json`;:ref:`to_json` + text;`HTML `__;:ref:`read_html`;:ref:`to_html` + text; Local clipboard;:ref:`read_clipboard`;:ref:`to_clipboard` + binary;`MS Excel `__;:ref:`read_excel`;:ref:`to_excel` + binary;`HDF5 Format `__;:ref:`read_hdf`;:ref:`to_hdf` + binary;`Feather Format `__;:ref:`read_feather`;:ref:`to_feather` + binary;`Msgpack `__;:ref:`read_msgpack`;:ref:`to_msgpack` + binary;`Stata `__;:ref:`read_stata`;:ref:`to_stata` + binary;`SAS `__;:ref:`read_sas`; + binary;`Python Pickle Format `__;:ref:`read_pickle`;:ref:`to_pickle` + SQL;`SQL `__;:ref:`read_sql`;:ref:`to_sql` + SQL;`Google Big Query `__;:ref:`read_gbq`;:ref:`to_gbq` :ref:`Here ` is an informal performance comparison for some of these IO methods.