DOC: behavior when slicing with missing bounds

closes pandas-dev#16917

doc/source/indexing.rst

@@ -78,8 +78,9 @@ of multi-axis indexing.
     *label* of the index. This use is **not** an integer position along the
     index)
   - A list or array of labels ``['a', 'b', 'c']``
-  - A slice object with labels ``'a':'f'``, (note that contrary to usual python
-    slices, **both** the start and the stop are included!)
+  - A slice object with labels ``'a':'f'`` (note that contrary to usual python
+    slices, **both** the start and the stop are included, when present in the
+    index!)
   - A boolean array
   - A ``callable`` function with one argument (the calling Series, DataFrame or Panel) and
     that returns valid output for indexing (one of the above)
@@ -330,13 +331,15 @@ Selection By Label
      dfl.loc['20130102':'20130104']
 
 pandas provides a suite of methods in order to have **purely label based indexing**. This is a strict inclusion based protocol.
-**At least 1** of the labels for which you ask, must be in the index or a ``KeyError`` will be raised! When slicing, the start bound is *included*, **AND** the stop bound is *included*. Integers are valid labels, but they refer to the label **and not the position**.
+**At least 1** of the labels for which you ask, must be in the index or a ``KeyError`` will be raised! When slicing, both the start bound **AND** the stop bound are *included*, if present in the index. Integers are valid labels, but they refer to the label **and not the position**.
 
 The ``.loc`` attribute is the primary access method. The following are valid inputs:
 
 - A single label, e.g. ``5`` or ``'a'``, (note that ``5`` is interpreted as a *label* of the index. This use is **not** an integer position along the index)
 - A list or array of labels ``['a', 'b', 'c']``
-- A slice object with labels ``'a':'f'`` (note that contrary to usual python slices, **both** the start and the stop are included!)
+- A slice object with labels ``'a':'f'`` (note that contrary to usual python
+  slices, **both** the start and the stop are included, when present in the
+  index!)
 - A boolean array
 - A ``callable``, see :ref:`Selection By Callable <indexing.callable>`
 
@@ -370,6 +373,15 @@ Accessing via label slices
 
    df1.loc['d':, 'A':'C']
 
+.. warning::
+
+   If both the start and the stop labels are present in the index, then
+   elements *located* between the two (including them) are returned. If at
+   least one of the two is absent but the index is sorted (and can be compared
+   against start and stop labels), then slicing will still work, by selecting
+   labels which *rank* between the two. However, if at least one of the two is
+   absent *and* the index is not sorted, a ``TypeError`` will be raised.
+
 For getting a cross section using a label (equiv to ``df.xs('a')``)
 
 .. ipython:: python