remove last references to v0.18 in docs and code (#27507)

Author: topper-123

doc/source/user_guide/advanced.rst

@@ -810,15 +810,10 @@ values **not** in the categories, similarly to how you can reindex **any** panda
 Int64Index and RangeIndex
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. warning::
-
-   Indexing on an integer-based Index with floats has been clarified in 0.18.0, for a summary of the changes, see :ref:`here <whatsnew_0180.float_indexers>`.
-
-:class:`Int64Index` is a fundamental basic index in pandas.
-This is an immutable array implementing an ordered, sliceable set.
-Prior to 0.18.0, the ``Int64Index`` would provide the default index for all ``NDFrame`` objects.
+:class:`Int64Index` is a fundamental basic index in pandas. This is an immutable array
+implementing an ordered, sliceable set.
 
-:class:`RangeIndex` is a sub-class of ``Int64Index`` added in version 0.18.0, now providing the default index for all ``NDFrame`` objects.
+:class:`RangeIndex` is a sub-class of ``Int64Index``  that provides the default index for all ``NDFrame`` objects.
 ``RangeIndex`` is an optimized version of ``Int64Index`` that can represent a monotonic ordered set. These are analogous to Python `range types <https://docs.python.org/3/library/stdtypes.html#typesseq-range>`__.
 
 .. _indexing.float64index:
@@ -880,16 +875,6 @@ In non-float indexes, slicing using floats will raise a ``TypeError``.
    In [1]: pd.Series(range(5))[3.5:4.5]
    TypeError: the slice start [3.5] is not a proper indexer for this index type (Int64Index)
 
-.. warning::
-
-   Using a scalar float indexer for ``.iloc`` has been removed in 0.18.0, so the following will raise a ``TypeError``:
-
-   .. code-block:: ipython
-
-      In [3]: pd.Series(range(5)).iloc[3.0]
-      TypeError: cannot do positional indexing on <class 'pandas.indexes.range.RangeIndex'> with these indexers [3.0] of <type 'float'>
-
-
 Here is a typical use-case for using this type of indexing. Imagine that you have a somewhat
 irregular timedelta-like indexing scheme, but the data is recorded as floats. This could, for
 example, be millisecond offsets.

doc/source/user_guide/computation.rst

@@ -893,10 +893,9 @@ Therefore, there is an assumption that :math:`x_0` is not an ordinary value
 but rather an exponentially weighted moment of the infinite series up to that
 point.
 
-One must have :math:`0 < \alpha \leq 1`, and while since version 0.18.0
-it has been possible to pass :math:`\alpha` directly, it's often easier
-to think about either the **span**, **center of mass (com)** or **half-life**
-of an EW moment:
+One must have :math:`0 < \alpha \leq 1`, and while it is possible to pass
+:math:`\alpha` directly, it's often easier to think about either the
+**span**, **center  of mass (com)** or **half-life** of an EW moment:
 
 .. math::
 

doc/source/user_guide/enhancingperf.rst

@@ -628,8 +628,6 @@ new or modified columns is returned and the original frame is unchanged.
    df.eval('e = a - c', inplace=False)
    df
 
-.. versionadded:: 0.18.0
-
 As a convenience, multiple assignments can be performed by using a
 multi-line string.
 

doc/source/user_guide/indexing.rst

@@ -36,10 +36,6 @@ this area.
    should be avoided. See :ref:`Returning a View versus Copy
    <indexing.view_versus_copy>`.
 
-.. warning::
-
-   Indexing on an integer-based Index with floats has been clarified in 0.18.0, for a summary of the changes, see :ref:`here <whatsnew_0180.float_indexers>`.
-
 See the :ref:`MultiIndex / Advanced Indexing <advanced>` for ``MultiIndex`` and more advanced indexing documentation.
 
 See the :ref:`cookbook<cookbook.selection>` for some advanced strategies.
@@ -83,8 +79,6 @@ of multi-axis indexing.
     * A ``callable`` function with one argument (the calling Series or DataFrame) and
       that returns valid output for indexing (one of the above).
 
-      .. versionadded:: 0.18.1
-
   See more at :ref:`Selection by Position <indexing.integer>`,
   :ref:`Advanced Indexing <advanced>` and :ref:`Advanced
   Hierarchical <advanced.advanced_hierarchical>`.
@@ -1101,9 +1095,7 @@ This is equivalent to (but faster than) the following.
    df2 = df.copy()
    df.apply(lambda x, y: x.where(x > 0, y), y=df['A'])
 
-.. versionadded:: 0.18.1
-
-Where can accept a callable as condition and ``other`` arguments. The function must
+``where`` can accept a callable as condition and ``other`` arguments. The function must
 be with one argument (the calling Series or DataFrame) and that returns valid output
 as condition and ``other`` argument.
 

doc/source/user_guide/io.rst

@@ -296,7 +296,6 @@ compression : {``'infer'``, ``'gzip'``, ``'bz2'``, ``'zip'``, ``'xz'``, ``None``
   the ZIP file must contain only one data file to be read in.
   Set to ``None`` for no decompression.
 
-  .. versionadded:: 0.18.1 support for 'zip' and 'xz' compression.
   .. versionchanged:: 0.24.0 'infer' option added and set to default.
 thousands : str, default ``None``
   Thousands separator.

doc/source/user_guide/reshaping.rst

@@ -484,8 +484,6 @@ not contain any instances of a particular category.
 Normalization
 ~~~~~~~~~~~~~
 
-.. versionadded:: 0.18.1
-
 Frequency tables can also be normalized to show percentages rather than counts
 using the ``normalize`` argument:
 

doc/source/user_guide/style.ipynb

@@ -6,10 +6,6 @@
    "source": [
     "# Styling\n",
     "\n",
-    "*New in version 0.17.1*\n",
-    "\n",
-    "<span style=\"color: red\">*Provisional: This is a new feature and still under development. We'll be adding features and possibly making breaking changes in future releases. We'd love to hear your feedback.*</span>\n",
-    "\n",
     "This document is written as a Jupyter Notebook, and can be viewed or downloaded [here](http://nbviewer.ipython.org/github/pandas-dev/pandas/blob/master/doc/source/style.ipynb).\n",
     "\n",
     "You can apply **conditional formatting**, the visual styling of a DataFrame\n",

doc/source/user_guide/text.rst

@@ -366,13 +366,12 @@ Extract first match in each subject (extract)
 
 .. warning::
 
-   In version 0.18.0, ``extract`` gained the ``expand`` argument. When
-   ``expand=False`` it returns a ``Series``, ``Index``, or
+   Before version 0.23, argument ``expand`` of the ``extract`` method defaulted to
+   ``False``. When ``expand=False``, ``expand`` returns a ``Series``, ``Index``, or
    ``DataFrame``, depending on the subject and regular expression
-   pattern (same behavior as pre-0.18.0). When ``expand=True`` it
-   always returns a ``DataFrame``, which is more consistent and less
-   confusing from the perspective of a user. ``expand=True`` is the
-   default since version 0.23.0.
+   pattern. When ``expand=True``, it always returns a ``DataFrame``,
+   which is more consistent and less confusing from the perspective of a user.
+   ``expand=True`` has been the default since version 0.23.0.
 
 The ``extract`` method accepts a `regular expression
 <https://docs.python.org/3/library/re.html>`__ with at least one
@@ -468,8 +467,6 @@ Extract all matches in each subject (extractall)
 
 .. _text.extractall:
 
-.. versionadded:: 0.18.0
-
 Unlike ``extract`` (which returns only the first match),
 
 .. ipython:: python

doc/source/user_guide/timeseries.rst

@@ -607,8 +607,6 @@ We are stopping on the included end-point as it is part of the index:
 
    dft['2013-1-15':'2013-1-15 12:30:00']
 
-.. versionadded:: 0.18.0
-
 ``DatetimeIndex`` partial string indexing also works on a ``DataFrame`` with a ``MultiIndex``:
 
 .. ipython:: python
@@ -1514,11 +1512,6 @@ Converting to Python datetimes
 Resampling
 ----------
 
-.. warning::
-
-   The interface to ``.resample`` has changed in 0.18.0 to be more groupby-like and hence more flexible.
-   See the :ref:`whatsnew docs <whatsnew_0180.breaking.resample>` for a comparison with prior versions.
-
 Pandas has a simple, powerful, and efficient functionality for performing
 resampling operations during frequency conversion (e.g., converting secondly
 data into 5-minutely data). This is extremely common in, but not limited to,
@@ -1528,8 +1521,8 @@ financial applications.
 on each of its groups. See some :ref:`cookbook examples <cookbook.resample>` for
 some advanced strategies.
 
-Starting in version 0.18.1, the ``resample()`` function can be used directly from
-``DataFrameGroupBy`` objects, see the :ref:`groupby docs <groupby.transform.window_resample>`.
+The ``resample()`` method can be used directly from ``DataFrameGroupBy`` objects,
+see the :ref:`groupby docs <groupby.transform.window_resample>`.
 
 .. note::
 

doc/source/user_guide/visualization.rst

@@ -1632,18 +1632,3 @@ when plotting a large number of points.
    :suppress:
 
     plt.close('all')
-
-
-.. _rplot:
-
-
-Trellis plotting interface
---------------------------
-
-.. warning::
-
-    The ``rplot`` trellis plotting interface has been **removed**. Please use
-    external packages like `seaborn <https://github.com/mwaskom/seaborn>`_ for
-    similar but more refined functionality and refer to our 0.18.1 documentation
-    `here <http://pandas.pydata.org/pandas-docs/version/0.18.1/visualization.html>`__
-    for how to convert to using it.