DataFrame self-joins
Given the following DataFrame

| area | point | test | value |
| --- | --- | --- | --- |
| A | 11 | 0 | 1234234 |
| A | 11 | 1 | 12341234 |
| A | 16 | 0 | 234234 |
| A | 16 | 1 | 2343 |
| A | 16 | 2 | 234234 |
| C | 4 | 0 | 234234 |
| C | 4 | 1 | 234234 |

it would be nice if there were a way of grouping say columns `area` and `point` and comparing the `value` per `test` > 1 with the value for `test` - 1. 

This can be done by iterating over `df.groupby(['area', 'point', 'test'])` and using the sorting provided by `groupby()` on the specified columns to compare current and previous `value`s.  However, it would be neat if this could also be done in a more Pandas-esque way using something akin to a SQL self-join.

NB request first made in pystatsmodels Google Group; was asked by Wes to create a Github issue for this.
