DOC/CLN: remove versionadded/changed:: 0.23 (#36338)

Author: simonjayhawkins

doc/source/development/extending.rst

@@ -73,8 +73,6 @@ applies only to certain dtypes.
 Extension types
 ---------------
 
-.. versionadded:: 0.23.0
-
 .. warning::
 
    The :class:`pandas.api.extensions.ExtensionDtype` and :class:`pandas.api.extensions.ExtensionArray` APIs are new and

doc/source/getting_started/install.rst

@@ -301,8 +301,6 @@ Optional dependencies for parsing HTML
 One of the following combinations of libraries is needed to use the
 top-level :func:`~pandas.read_html` function:
 
-.. versionchanged:: 0.23.0
-
 * `BeautifulSoup4`_ and `html5lib`_
 * `BeautifulSoup4`_ and `lxml`_
 * `BeautifulSoup4`_ and `html5lib`_ and `lxml`_

doc/source/user_guide/advanced.rst

@@ -1065,8 +1065,6 @@ are closed on.  Intervals are closed on the right side by default.
 
    pd.interval_range(start=0, end=4, closed='neither')
 
-.. versionadded:: 0.23.0
-
 Specifying ``start``, ``end``, and ``periods`` will generate a range of evenly spaced
 intervals from ``start`` to ``end`` inclusively, with ``periods`` number of elements
 in the resulting ``IntervalIndex``:

doc/source/user_guide/basics.rst

@@ -1877,8 +1877,6 @@ different columns.
 By indexes and values
 ~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 0.23.0
-
 Strings passed as the ``by`` parameter to :meth:`DataFrame.sort_values` may
 refer to either columns or index level names.
 

doc/source/user_guide/categorical.rst

@@ -112,8 +112,6 @@ only labels present in a given column are categories:
     df['B']
 
 
-.. versionadded:: 0.23.0
-
 Analogously, all columns in an existing ``DataFrame`` can be batch converted using :meth:`DataFrame.astype`:
 
 .. ipython:: python

doc/source/user_guide/dsintro.rst

@@ -597,8 +597,6 @@ to be inserted (for example, a ``Series`` or NumPy array), or a function
 of one argument to be called on the ``DataFrame``. A *copy* of the original
 DataFrame is returned, with the new values inserted.
 
-.. versionchanged:: 0.23.0
-
 Starting with Python 3.6 the order of ``**kwargs`` is preserved. This allows
 for *dependent* assignment, where an expression later in ``**kwargs`` can refer
 to a column created earlier in the same :meth:`~DataFrame.assign`.

doc/source/user_guide/io.rst

@@ -2360,8 +2360,6 @@ A few notes on the generated table schema:
       then ``level_<i>`` is used.
 
 
-.. versionadded:: 0.23.0
-
 ``read_json`` also accepts ``orient='table'`` as an argument. This allows for
 the preservation of metadata such as dtypes and index names in a
 round-trippable manner.

doc/source/user_guide/merging.rst

@@ -175,8 +175,6 @@ behavior:
 
 .. warning::
 
-   .. versionchanged:: 0.23.0
-
    The default behavior with ``join='outer'`` is to sort the other axis
    (columns in this case). In a future version of pandas, the default will
    be to not sort. We specified ``sort=False`` to opt in to the new
@@ -1198,8 +1196,6 @@ done using the following code.
 Merging on a combination of columns and index levels
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 0.23
-
 Strings passed as the ``on``, ``left_on``, and ``right_on`` parameters
 may refer to either column names or index level names.  This enables merging
 ``DataFrame`` instances on a combination of index levels and columns without

doc/source/user_guide/missing_data.rst

@@ -336,10 +336,6 @@ examined :ref:`in the API <api.dataframe.missing>`.
 Interpolation
 ~~~~~~~~~~~~~
 
-.. versionadded:: 0.23.0
-
-  The ``limit_area`` keyword argument was added.
-
 Both Series and DataFrame objects have :meth:`~DataFrame.interpolate`
 that, by default, performs linear interpolation at missing data points.
 
@@ -507,8 +503,8 @@ By default, ``NaN`` values are filled in a ``forward`` direction. Use
    ser.interpolate(limit_direction='both')
 
 By default, ``NaN`` values are filled whether they are inside (surrounded by)
-existing valid values, or outside existing valid values. Introduced in v0.23
-the ``limit_area`` parameter restricts filling to either inside or outside values.
+existing valid values, or outside existing valid values. The ``limit_area``
+parameter restricts filling to either inside or outside values.
 
 .. ipython:: python
 

doc/source/user_guide/reshaping.rst

@@ -679,8 +679,6 @@ To choose another dtype, use the ``dtype`` argument:
 
     pd.get_dummies(df, dtype=bool).dtypes
 
-.. versionadded:: 0.23.0
-
 
 .. _reshaping.factorize: