Merge pull request pandas-dev#10600 from jorisvandenbossche/doc-whatsnew-fixes

DOC: some formatting fixes in whatsnew

Author: jorisvandenbossche

doc/source/whatsnew/v0.11.0.txt

@@ -103,6 +103,7 @@ Conversion
 Mixed Conversion
 
 .. ipython:: python
+   :okwarning:
 
    df3['D'] = '1.'
    df3['E'] = '1'
@@ -116,6 +117,7 @@ Mixed Conversion
 Forcing Date coercion (and setting ``NaT`` when not datelike)
 
 .. ipython:: python
+   :okwarning:
 
    from datetime import datetime
    s = Series([datetime(2001,1,1,0,0), 'foo', 1.0, 1,
@@ -328,4 +330,3 @@ Enhancements
 See the :ref:`full release notes
 <release>` or issue tracker
 on GitHub for a complete list.
-

doc/source/whatsnew/v0.17.0.txt

@@ -86,20 +86,20 @@ Other enhancements
 Backwards incompatible API changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
+.. _whatsnew_0170.api_breaking.convert_objects:
+
 Changes to convert_objects
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. _whatsnew_0170.api_breaking.convert_objects:
-
 - ``DataFrame.convert_objects`` keyword arguments have been shortened. (:issue:`10265`)
 
-=====================   =============
-Old                     New
-=====================   =============
-``convert_dates``       ``datetime``
-``convert_numeric``     ``numeric``
-``convert_timedelta``   ``timedelta``
-=====================   =============
+  =====================   =============
+  Old                     New
+  =====================   =============
+  ``convert_dates``       ``datetime``
+  ``convert_numeric``     ``numeric``
+  ``convert_timedelta``   ``timedelta``
+  =====================   =============
 
 - Coercing types with ``DataFrame.convert_objects`` is now implemented using the
   keyword argument ``coerce=True``.  Previously types were coerced by setting a
@@ -152,14 +152,19 @@ Old                     New
   to do nothing, and so it is necessary to pass at least one conversion target
   in the method call.
 
+.. _whatsnew_0170.api_breaking.other:
+
+Other API Changes
+^^^^^^^^^^^^^^^^^
+
 - Operator equal on Index should behavior similarly to Series (:issue:`9947`)
 
-Starting in v0.17.0, comparing ``Index`` objects of different lengths will raise
-a ``ValueError``. This is to be consistent with the behavior of ``Series``.
+  Starting in v0.17.0, comparing ``Index`` objects of different lengths will raise
+  a ``ValueError``. This is to be consistent with the behavior of ``Series``.
 
-Previous behavior:
+  Previous behavior:
 
-.. code-block:: python
+  .. code-block:: python
 
    In [2]: pd.Index([1, 2, 3]) == pd.Index([1, 4, 5])
    Out[2]: array([ True, False, False], dtype=bool)
@@ -183,9 +188,9 @@ Previous behavior:
    In [7]: pd.Series([1, 2, 3]) == pd.Series([1, 2])
    ValueError: Series lengths must match to compare
 
-New behavior:
+  New behavior:
 
-.. code-block:: python
+  .. code-block:: python
 
    In [8]: pd.Index([1, 2, 3]) == pd.Index([1, 4, 5])
    Out[8]: array([ True, False, False], dtype=bool)
@@ -209,23 +214,19 @@ New behavior:
    In [13]: pd.Series([1, 2, 3]) == pd.Series([1, 2])
    ValueError: Series lengths must match to compare
 
-Note that this is different from the ``numpy`` behavior where a comparison can
-be broadcast:
+  Note that this is different from the ``numpy`` behavior where a comparison can
+  be broadcast:
 
-.. ipython:: python
+  .. ipython:: python
 
    np.array([1, 2, 3]) == np.array([1])
 
-or it can return False if broadcasting can not be done:
+  or it can return False if broadcasting can not be done:
 
-.. ipython:: python
+  .. ipython:: python
 
    np.array([1, 2, 3]) == np.array([1, 2])
 
-.. _whatsnew_0170.api_breaking.other:
-
-Other API Changes
-^^^^^^^^^^^^^^^^^
 - Enable writing Excel files in :ref:`memory <_io.excel_writing_buffer>` using StringIO/BytesIO (:issue:`7074`)
 - Enable serialization of lists and dicts to strings in ExcelWriter (:issue:`8188`)
 - Allow passing `kwargs` to the interpolation methods (:issue:`10378`).
@@ -265,8 +266,8 @@ as well as the ``.sum()`` operation.
 
 Releasing of the GIL could benefit an application that uses threads for user interactions (e.g. ``QT``), or performaning multi-threaded computations. A nice example of a library that can handle these types of computation-in-parallel is the dask_ library.
 
-.. _whatsnew_0170.performance:
 
+.. _whatsnew_0170.performance:
 
 Performance Improvements
 ~~~~~~~~~~~~~~~~~~~~~~~~
@@ -278,6 +279,7 @@ Performance Improvements
 - Improved performance of ``Series.isin`` for datetimelike/integer Series (:issue:`10287`)
 - 20x improvement in ``concat`` of Categoricals when categories are identical (:issue:`10587`)
 
+
 .. _whatsnew_0170.bug_fixes:
 
 Bug Fixes