Smoke Testing
Was thinking on writing smoke tests for Series and DataFrame. Idea is to have "it works"-style of tests on all methods of Series (and later also For DataFrame) for all combinations of index type, value type, and possible input argument combinations.

Current code is certainly not intended to be merged in, just want to introduce the idea.
Smoke tests are easy/quick to write and i think can avoid issues like "method x works fine for y-dtype but unexpectedly raises exception for z-dtype".

Of course it is better to have verification of the output also, and not only check "it works" for all possible cases, but that is much more work and (maybe) for a second phase.

For now, one of the tests _smoking_ `__eq__`, this came out:

``` python
In [17]: s1 = pandas.Series(['foo', 'bar', 'baz'])

In [18]: s2 = pandas.Series()

In [19]: s2 == s1
Out[19]: Series([], dtype=bool)

In [20]: s1 == s2
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
...
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'double'
```
