Question / Possibly a Feature request: comparison machinery for unit tests
When it comes to writing unit tests that return a `DataFrame` or a `TimeSeries` there's a clear need to compare the output to the expected result. The comparison can be strict, or relaxed in terms of the order of columns and/or order of rows, and could also be forgiving for floats.

I'm thinking of an approach implemented in https://pythonhosted.org/toytable/toytable.table.html#table-literals, i.e. defining a table as 

``` python
>>> pokedex = table_literal("""
...     | Pokemon (str) | Level (int) | Owner (str) | Type (str) |
...     | Pikchu        | 12          | Ash Ketchum | Electric   |
...     | Bulbasaur     | 16          | Ash Ketchum | Grass      |
...     | Charmander    | 19          | Ash Ketchum | Fire       |
...     | Raichu        | 23          | Lt. Surge   | Electric   |
...     """)
```

and subsequently invoking `self.assertTableEqual` or `self.assertTableContentsEqual`.

Does anything similar exist in pandas (I could not find), and can the above approach be upvoted please?
