warnings in docs

Author: jreback

doc/source/user_guide/io.rst

@@ -3401,6 +3401,7 @@ both on the writing (serialization), and reading (deserialization).
    :func:`read_msgpack` is only guaranteed backwards compatible back to pandas version 0.20.3
 
 .. ipython:: python
+   :okwarning:
 
    df = pd.DataFrame(np.random.rand(5, 2), columns=list('AB'))
    df.to_msgpack('foo.msg')
@@ -3410,20 +3411,23 @@ both on the writing (serialization), and reading (deserialization).
 You can pass a list of objects and you will receive them back on deserialization.
 
 .. ipython:: python
+   :okwarning:
 
    pd.to_msgpack('foo.msg', df, 'foo', np.array([1, 2, 3]), s)
    pd.read_msgpack('foo.msg')
 
 You can pass ``iterator=True`` to iterate over the unpacked results:
 
 .. ipython:: python
+   :okwarning:
 
    for o in pd.read_msgpack('foo.msg', iterator=True):
        print(o)
 
 You can pass ``append=True`` to the writer to append to an existing pack:
 
 .. ipython:: python
+   :okwarning:
 
    df.to_msgpack('foo.msg', append=True)
    pd.read_msgpack('foo.msg')
@@ -3434,6 +3438,7 @@ can pack arbitrary collections of Python lists, dicts, scalars, while intermixin
 pandas objects.
 
 .. ipython:: python
+   :okwarning:
 
    pd.to_msgpack('foo2.msg', {'dict': [{'df': df}, {'string': 'foo'},
                                        {'scalar': 1.}, {'s': s}]})
@@ -3452,12 +3457,14 @@ Read/write API
 Msgpacks can also be read from and written to strings.
 
 .. ipython:: python
+   :okwarning:
 
    df.to_msgpack()
 
 Furthermore you can concatenate the strings to produce a list of the original objects.
 
 .. ipython:: python
+   :okwarning:
 
   pd.read_msgpack(df.to_msgpack() + s.to_msgpack())
 

doc/source/whatsnew/v0.13.0.rst

@@ -829,6 +829,7 @@ Experimental
      Since this is an EXPERIMENTAL LIBRARY, the storage format may not be stable until a future release.
 
   .. ipython:: python
+     :okwarning:
 
      df = pd.DataFrame(np.random.rand(5, 2), columns=list('AB'))
      df.to_msgpack('foo.msg')
@@ -841,6 +842,7 @@ Experimental
   You can pass ``iterator=True`` to iterator over the unpacked results
 
   .. ipython:: python
+     :okwarning:
 
      for o in pd.read_msgpack('foo.msg', iterator=True):
          print(o)