df.sortlevel() vs df.sort_index()
**Q1**: For a multi-index dataframe, what is the difference between `sortlevel()` and `sort_index()`?

As far as I can tell, for a dataframe like:

```
  df = pd.DataFrame({'A' : [np.random.random_integers(10) for x in xrange(500)], 
                     'B' : [np.random.random_integers(10) for x in xrange(500)], 
                     'C' : [np.random.random_integers(10) for x in xrange(500)],
                     'data' : randn(500) })
```

the result is the same.

**Q2**: Why do these methods not use the same [naming convention](http://en.wikipedia.org/wiki/Naming_convention_%28programming%29#Multiple-word_identifiers)? `sort_index` uses underscore to separate words, while `sortlevel` is just one word.

What is the official convention in Pandas? Isn't the [Python convention to use underscore splitting?](http://stackoverflow.com/a/159745/1732769) 
