Deprecation/FutureWarnings raised by `==` on NumPy arrays in NumPy version1.9
This continues a discussion started at the end of GH 8512

Summary: NumPy is changing the behavior of `==`. It no longer checks for `is` relationships between elements. Therefore,

In older versions of NumPy:

> > > array([nan], dtype=object) == array([nan], dtype=object)
> > > array([ True], dtype=bool)

In future NumPy, I think this will happen:

> > > array([nan], dtype=object) == array([nan], dtype=object)
> > > array([ False], dtype=bool)

In current NumPy version 1.9, a DeprecationWarning or FutureWarning is issued.

One place where this issue affects Pandas is 

nosetests -v pandas/tests/test_series.py:TestSeries.test_replace

The problem originates in internals.py/_possibly_compare which is called like this:

```
_possibly_compare(np.array([1, np.nan], dtype='O'), 'foo', operater.eq)
_possibly_compare(np.array(['2000-01-02T19:00'], dtype='datetime64[ns]'), 1, operater.eq)
```

Both of these raise DeprecationWarnings. 

`a` is always an array, `b` is a scalar. AFAICT, the intent of
`_possibly_compare` is to return a boolean mask where elements in `a` equal `b`.
Since we want a boolean mask, `array_equivalent` is not a help here since that
just returns a single bool. 
