DOC: Small whatsnew fixes

doc/source/whatsnew/v0.24.0.rst

@@ -1128,7 +1128,7 @@ update the ``ExtensionDtype._metadata`` tuple to match the signature of your
 - :meth:`~Series.shift` now dispatches to :meth:`ExtensionArray.shift` (:issue:`22386`)
 - :meth:`Series.combine()` works correctly with :class:`~pandas.api.extensions.ExtensionArray` inside of :class:`Series` (:issue:`20825`)
 - :meth:`Series.combine()` with scalar argument now works for any function type (:issue:`21248`)
-- :meth:`Series.astype` and :meth:`DataFrame.astype` now dispatch to :meth:`ExtensionArray.astype` (:issue:`21185:`).
+- :meth:`Series.astype` and :meth:`DataFrame.astype` now dispatch to :meth:`ExtensionArray.astype` (:issue:`21185`).
 - Slicing a single row of a ``DataFrame`` with multiple ExtensionArrays of the same type now preserves the dtype, rather than coercing to object (:issue:`22784`)
 - Bug when concatenating multiple ``Series`` with different extension dtypes not casting to object dtype (:issue:`22994`)
 - Series backed by an ``ExtensionArray`` now work with :func:`util.hash_pandas_object` (:issue:`23066`)
@@ -1261,7 +1261,7 @@ Other API Changes
 - The order of the arguments of :func:`DataFrame.to_html` and :func:`DataFrame.to_string` is rearranged to be consistent with each other. (:issue:`23614`)
 - :meth:`CategoricalIndex.reindex` now raises a ``ValueError`` if the target index is non-unique and not equal to the current index. It previously only raised if the target index was not of a categorical dtype (:issue:`23963`).
 - :func:`Series.to_list` and :func:`Index.to_list` are now aliases of ``Series.tolist`` respectively ``Index.tolist`` (:issue:`8826`)
-- The result of ``SparseSeries.unstack`` is now a :class:`DataFrame` with sparse values, rather than a :class:`SparseDataFrame` (issue:`24372`).
+- The result of ``SparseSeries.unstack`` is now a :class:`DataFrame` with sparse values, rather than a :class:`SparseDataFrame` (:issue:`24372`).
 
 .. _whatsnew_0240.deprecations:
 
@@ -1300,15 +1300,15 @@ Deprecations
 - The ``keep_tz=False`` option (the default) of the ``keep_tz`` keyword of
   :meth:`DatetimeIndex.to_series` is deprecated (:issue:`17832`).
 - Timezone converting a tz-aware ``datetime.datetime`` or :class:`Timestamp` with :class:`Timestamp` and the ``tz`` argument is now deprecated. Instead, use :meth:`Timestamp.tz_convert` (:issue:`23579`)
-- :func:`pandas.api.types.is_period` is deprecated in favor of `pandas.api.types.is_period_dtype` (:issue:`23917`)
-- :func:`pandas.api.types.is_datetimetz` is deprecated in favor of `pandas.api.types.is_datetime64tz` (:issue:`23917`)
+- :func:`pandas.api.types.is_period` is deprecated in favor of ``pandas.api.types.is_period_dtype`` (:issue:`23917`)
+- :func:`pandas.api.types.is_datetimetz` is deprecated in favor of ``pandas.api.types.is_datetime64tz`` (:issue:`23917`)
 - Creating a :class:`TimedeltaIndex`, :class:`DatetimeIndex`, or :class:`PeriodIndex` by passing range arguments `start`, `end`, and `periods` is deprecated in favor of :func:`timedelta_range`, :func:`date_range`, or :func:`period_range` (:issue:`23919`)
 - Passing a string alias like ``'datetime64[ns, UTC]'`` as the ``unit`` parameter to :class:`DatetimeTZDtype` is deprecated. Use :class:`DatetimeTZDtype.construct_from_string` instead (:issue:`23990`).
 - The ``skipna`` parameter of :meth:`~pandas.api.types.infer_dtype` will switch to ``True`` by default in a future version of pandas (:issue:`17066`, :issue:`24050`)
 - In :meth:`Series.where` with Categorical data, providing an ``other`` that is not present in the categories is deprecated. Convert the categorical to a different dtype or add the ``other`` to the categories first (:issue:`24077`).
 - :meth:`Series.clip_lower`, :meth:`Series.clip_upper`, :meth:`DataFrame.clip_lower` and :meth:`DataFrame.clip_upper` are deprecated and will be removed in a future version. Use ``Series.clip(lower=threshold)``, ``Series.clip(upper=threshold)`` and the equivalent ``DataFrame`` methods (:issue:`24203`)
 - :meth:`Series.nonzero` is deprecated and will be removed in a future version (:issue:`18262`)
-- Passing an integer to :meth:`Series.fillna` and :meth:`DataFrame.fillna` with ``timedelta64[ns]`` dtypes is deprecated, will raise ``TypeError`` in a future version.  Use ``obj.fillna(pd.Timedelta(...))` instead (:issue:`24694`)
+- Passing an integer to :meth:`Series.fillna` and :meth:`DataFrame.fillna` with ``timedelta64[ns]`` dtypes is deprecated, will raise ``TypeError`` in a future version.  Use ``obj.fillna(pd.Timedelta(...))`` instead (:issue:`24694`)
 
 .. _whatsnew_0240.deprecations.datetimelike_int_ops:
 
@@ -1525,7 +1525,7 @@ Performance Improvements
 - Improved performance of :meth:`~DataFrame.where` for Categorical data (:issue:`24077`)
 - Improved performance of iterating over a :class:`Series`. Using :meth:`DataFrame.itertuples` now creates iterators
   without internally allocating lists of all elements (:issue:`20783`)
-- Improved performance of :class:`Period` constructor, additionally benefitting ``PeriodArray`` and ``PeriodIndex`` creation (:issue:`24084` and :issue:`24118`)
+- Improved performance of :class:`Period` constructor, additionally benefitting ``PeriodArray`` and ``PeriodIndex`` creation (:issue:`24084`, :issue:`24118`)
 - Improved performance of tz-aware :class:`DatetimeArray` binary operations (:issue:`24491`)
 
 .. _whatsnew_0240.bug_fixes:
@@ -1671,7 +1671,7 @@ Numeric
 - Bug in :class:`DataFrame` with ``timedelta64[ns]`` dtype arithmetic operations with ``ndarray`` with integer dtype incorrectly treating the narray as ``timedelta64[ns]`` dtype (:issue:`23114`)
 - Bug in :meth:`Series.rpow` with object dtype ``NaN`` for ``1 ** NA`` instead of ``1`` (:issue:`22922`).
 - :meth:`Series.agg` can now handle numpy NaN-aware methods like :func:`numpy.nansum` (:issue:`19629`)
-- Bug in :meth:`Series.rank` and :meth:`DataFrame.rank` when ``pct=True`` and more than 2:sup:`24` rows are present resulted in percentages greater than 1.0 (:issue:`18271`)
+- Bug in :meth:`Series.rank` and :meth:`DataFrame.rank` when ``pct=True`` and more than 2\ :sup:`24` rows are present resulted in percentages greater than 1.0 (:issue:`18271`)
 - Calls such as :meth:`DataFrame.round` with a non-unique :meth:`CategoricalIndex` now return expected data. Previously, data would be improperly duplicated (:issue:`21809`).
 - Added ``log10``, `floor` and `ceil` to the list of supported functions in :meth:`DataFrame.eval` (:issue:`24139`, :issue:`24353`)
 - Logical operations ``&, |, ^`` between :class:`Series` and :class:`Index` will no longer raise ``ValueError`` (:issue:`22092`)
@@ -1758,7 +1758,7 @@ I/O
 - Bug in :meth:`read_excel()` when ``parse_cols`` is specified with an empty dataset (:issue:`9208`)
 - :func:`read_html()` no longer ignores all-whitespace ``<tr>`` within ``<thead>`` when considering the ``skiprows`` and ``header`` arguments. Previously, users had to decrease their ``header`` and ``skiprows`` values on such tables to work around the issue. (:issue:`21641`)
 - :func:`read_excel()` will correctly show the deprecation warning for previously deprecated ``sheetname`` (:issue:`17994`)
-- :func:`read_csv()` and func:`read_table()` will throw ``UnicodeError`` and not coredump on badly encoded strings (:issue:`22748`)
+- :func:`read_csv()` and :func:`read_table()` will throw ``UnicodeError`` and not coredump on badly encoded strings (:issue:`22748`)
 - :func:`read_csv()` will correctly parse timezone-aware datetimes (:issue:`22256`)
 - Bug in :func:`read_csv()` in which memory management was prematurely optimized for the C engine when the data was being read in chunks (:issue:`23509`)
 - Bug in :func:`read_csv()` in unnamed columns were being improperly identified when extracting a multi-index (:issue:`23687`)