Moved format documentation from code to docs (#420)

1 files changed, 0 insertions, 193 deletions

diff --git a/src/tablib/core.py b/src/tablib/core.py
index a5ea0b0..d17e1e8 100644
--- a/src/tablib/core.py
+++ b/src/tablib/core.py
@@ -424,199 +424,6 @@ class Dataset:
 
         return fmt.export_set(self, **kwargs)
 
-    # -------
-    # Formats
-    # -------
-
-    @property
-    def xls():
-        """A Legacy Excel Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.
-
-        .. note::
-
-            XLS files are limited to a maximum of 65,000 rows. Use :class:`Dataset.xlsx` to avoid this limitation.
-
-         .. admonition:: Binary Warning
-
-             :class:`Dataset.xls` contains binary data, so make sure to write in binary mode::
-
-                with open('output.xls', 'wb') as f:
-                    f.write(data.xls)
-        """
-        pass
-
-    @property
-    def xlsx():
-        """An Excel '07+ Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.
-
-         .. admonition:: Binary Warning
-
-             :class:`Dataset.xlsx` contains binary data, so make sure to write in binary mode::
-
-                with open('output.xlsx', 'wb') as f:
-                    f.write(data.xlsx)
-        """
-        pass
-
-    @property
-    def ods():
-        """An OpenDocument Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.
-
-         .. admonition:: Binary Warning
-
-             :class:`Dataset.ods` contains binary data, so make sure to write in binary mode::
-
-                with open('output.ods', 'wb') as f:
-                    f.write(data.ods)
-        """
-        pass
-
-    @property
-    def csv():
-        """A CSV representation of the :class:`Dataset` object. The top row will contain
-        headers, if they have been set. Otherwise, the top row will contain
-        the first row of the dataset.
-
-        A dataset object can also be imported by setting the :class:`Dataset.csv` attribute. ::
-
-            data = tablib.Dataset()
-            data.csv = 'age, first_name, last_name\\n90, John, Adams'
-
-        Import assumes (for now) that headers exist.
-
-        .. admonition:: Binary Warning for Python 2
-
-             :class:`Dataset.csv` uses \\r\\n line endings by default so, in Python 2, make
-             sure to write in binary mode::
-
-                 with open('output.csv', 'wb') as f:
-                     f.write(data.csv)
-
-             If you do not do this, and you export the file on Windows, your
-             CSV file will open in Excel with a blank line between each row.
-
-        .. admonition:: Line endings for Python 3
-
-             :class:`Dataset.csv` uses \\r\\n line endings by default so, in Python 3, make
-             sure to include newline='' otherwise you will get a blank line between each row
-             when you open the file in Excel::
-
-                 with open('output.csv', 'w', newline='') as f:
-                     f.write(data.csv)
-
-             If you do not do this, and you export the file on Windows, your
-             CSV file will open in Excel with a blank line between each row.
-        """
-        pass
-
-    @property
-    def tsv():
-        """A TSV representation of the :class:`Dataset` object. The top row will contain
-        headers, if they have been set. Otherwise, the top row will contain
-        the first row of the dataset.
-
-        A dataset object can also be imported by setting the :class:`Dataset.tsv` attribute. ::
-
-            data = tablib.Dataset()
-            data.tsv = 'age\tfirst_name\tlast_name\\n90\tJohn\tAdams'
-
-        Import assumes (for now) that headers exist.
-        """
-        pass
-
-    @property
-    def yaml():
-        """A YAML representation of the :class:`Dataset` object. If headers have been
-        set, a YAML list of objects will be returned. If no headers have
-        been set, a YAML list of lists (rows) will be returned instead.
-
-        A dataset object can also be imported by setting the :class:`Dataset.yaml` attribute: ::
-
-            data = tablib.Dataset()
-            data.yaml = '- {age: 90, first_name: John, last_name: Adams}'
-
-        Import assumes (for now) that headers exist.
-        """
-        pass
-
-    @property
-    def df():
-        """A DataFrame representation of the :class:`Dataset` object.
-
-        A dataset object can also be imported by setting the :class:`Dataset.df` attribute: ::
-
-            data = tablib.Dataset()
-            data.df = DataFrame(np.random.randn(6,4))
-
-        Import assumes (for now) that headers exist.
-        """
-        pass
-
-    @property
-    def json():
-        """A JSON representation of the :class:`Dataset` object. If headers have been
-        set, a JSON list of objects will be returned. If no headers have
-        been set, a JSON list of lists (rows) will be returned instead.
-
-        A dataset object can also be imported by setting the :class:`Dataset.json` attribute: ::
-
-            data = tablib.Dataset()
-            data.json = '[{"age": 90, "first_name": "John", "last_name": "Adams"}]'
-
-        Import assumes (for now) that headers exist.
-        """
-        pass
-
-    @property
-    def html():
-        """A HTML table representation of the :class:`Dataset` object. If
-        headers have been set, they will be used as table headers.
-
-        .. notice:: This method can be used for export only.
-        """
-        pass
-
-    @property
-    def dbf():
-        """A dBASE representation of the :class:`Dataset` object.
-
-        A dataset object can also be imported by setting the
-        :class:`Dataset.dbf` attribute. ::
-
-            # To import data from an existing DBF file:
-            data = tablib.Dataset()
-            data.dbf = open('existing_table.dbf', mode='rb').read()
-
-            # to import data from an ASCII-encoded bytestring:
-            data = tablib.Dataset()
-            data.dbf = '<bytestring of tabular data>'
-
-        .. admonition:: Binary Warning
-
-            :class:`Dataset.dbf` contains binary data, so make sure to write in binary mode::
-
-                with open('output.dbf', 'wb') as f:
-                    f.write(data.dbf)
-        """
-        pass
-
-    @property
-    def latex():
-        """A LaTeX booktabs representation of the :class:`Dataset` object. If a
-        title has been set, it will be exported as the table caption.
-
-        .. note:: This method can be used for export only.
-        """
-        pass
-
-    @property
-    def jira():
-        """A Jira table representation of the :class:`Dataset` object.
-
-        .. note:: This method can be used for export only.
-        """
-        pass
-
     # ----
     # Rows
     # ----