Updated documentation for issue 4484.

Author: prossahl

doc/source/basics.rst

@@ -724,16 +724,16 @@ We illustrate these fill methods on a simple TimeSeries:
    ts2.reindex(ts.index, method='ffill')
    ts2.reindex(ts.index, method='bfill')
 
+Note these methods require that the indexes are **order increasing**.
+
 Note the same result could have been achieved using :ref:`fillna
 <missing_data.fillna>`:
 
 .. ipython:: python
 
    ts2.reindex(ts.index).fillna(method='ffill')
 
-Note these methods generally assume that the indexes are **sorted**. They may
-be modified in the future to be a bit more flexible but as time series data is
-ordered most of the time anyway, this has not been a major priority.
+Note that this method does not check the order of the index.
 
 .. _basics.drop:
 

doc/source/missing_data.rst

@@ -205,6 +205,9 @@ To remind you, these are the available filling methods:
 With time series data, using pad/ffill is extremely common so that the "last
 known value" is available at every time point.
 
+The ``ffill()`` function is equivalent to ``fillna(method='ffill')``
+and ``bfill()`` is equivalent to ``fillna(method='bfill')``
+
 .. _missing_data.dropna:
 
 Dropping axis labels with missing data: dropna

doc/source/release.rst

@@ -50,6 +50,8 @@ pandas 0.13
 
 **API Changes**
 
+  - ``DataFrame.reindex()`` and forward/backward filling now raises ValueError
+    if either index is not monotonic (:issue: `4484`).
   - ``pandas`` now is Python 2/3 compatible without the need for 2to3 thanks to
     @jtratner. As a result, pandas now uses iterators more extensively. This
     also led to the introduction of substantive parts of the Benjamin