Update deprecation warnings, which were already removed (#36292)

Author: phofl

doc/source/user_guide/indexing.rst

@@ -313,8 +313,10 @@ Selection by label
 
 .. warning::
 
-   Starting in 0.21.0, pandas will show a ``FutureWarning`` if indexing with a list with missing labels. In the future
-   this will raise a ``KeyError``. See :ref:`list-like Using loc with missing keys in a list is Deprecated <indexing.deprecate_loc_reindex_listlike>`.
+   .. versionchanged:: 1.0.0
+
+   Pandas will raise a ``KeyError`` if indexing with a list with missing labels. See :ref:`list-like Using loc with
+   missing keys in a list is Deprecated <indexing.deprecate_loc_reindex_listlike>`.
 
 pandas provides a suite of methods in order to have **purely label based indexing**. This is a strict inclusion based protocol.
 Every label asked for must be in the index, or a ``KeyError`` will be raised.
@@ -578,8 +580,9 @@ IX indexer is deprecated
 
 .. warning::
 
-   Starting in 0.20.0, the ``.ix`` indexer is deprecated, in favor of the more strict ``.iloc``
-   and ``.loc`` indexers.
+   .. versionchanged:: 1.0.0
+
+   The ``.ix`` indexer was removed, in favor of the more strict ``.iloc`` and ``.loc`` indexers.
 
 ``.ix`` offers a lot of magic on the inference of what the user wants to do. To wit, ``.ix`` can decide
 to index *positionally* OR via *labels* depending on the data type of the index. This has caused quite a
@@ -636,11 +639,13 @@ Indexing with list with missing labels is deprecated
 
 .. warning::
 
-   Starting in 0.21.0, using ``.loc`` or ``[]`` with a list with one or more missing labels, is deprecated, in favor of ``.reindex``.
+   .. versionchanged:: 1.0.0
+
+   Using ``.loc`` or ``[]`` with a list with one or more missing labels will no longer reindex, in favor of ``.reindex``.
 
 In prior versions, using ``.loc[list-of-labels]`` would work as long as *at least 1* of the keys was found (otherwise it
-would raise a ``KeyError``). This behavior is deprecated and will show a warning message pointing to this section. The
-recommended alternative is to use ``.reindex()``.
+would raise a ``KeyError``). This behavior was changed and will now raise a ``KeyError`` if at least one label is missing.
+The recommended alternative is to use ``.reindex()``.
 
 For example.
 

doc/source/user_guide/io.rst

@@ -3024,19 +3024,12 @@ It is often the case that users will insert columns to do temporary computations
 in Excel and you may not want to read in those columns. ``read_excel`` takes
 a ``usecols`` keyword to allow you to specify a subset of columns to parse.
 
-.. deprecated:: 0.24.0
+.. versionchanged:: 1.0.0
 
-Passing in an integer for ``usecols`` has been deprecated. Please pass in a list
+Passing in an integer for ``usecols`` will no longer work. Please pass in a list
 of ints from 0 to ``usecols`` inclusive instead.
 
-If ``usecols`` is an integer, then it is assumed to indicate the last column
-to be parsed.
-
-.. code-block:: python
-
-   pd.read_excel('path_to_file.xls', 'Sheet1', usecols=2)
-
-You can also specify a comma-delimited set of Excel columns and ranges as a string:
+You can specify a comma-delimited set of Excel columns and ranges as a string:
 
 .. code-block:: python
 

doc/source/user_guide/timeseries.rst

@@ -327,11 +327,11 @@ which can be specified. These are computed from the starting point specified by
    that was discussed :ref:`above<timeseries.converting.format>`). The
    available units are listed on the documentation for :func:`pandas.to_datetime`.
 
+.. versionchanged:: 1.0.0
+
 Constructing a :class:`Timestamp` or :class:`DatetimeIndex` with an epoch timestamp
-with the ``tz`` argument specified will currently localize the epoch timestamps to UTC
-first then convert the result to the specified time zone. However, this behavior
-is :ref:`deprecated <whatsnew_0240.deprecations.integer_tz>`, and if you have
-epochs in wall time in another timezone, it is recommended to read the epochs
+with the ``tz`` argument specified will raise a ValueError. If you have
+epochs in wall time in another timezone, you can read the epochs
 as timezone-naive timestamps and then localize to the appropriate timezone:
 
 .. ipython:: python