BUG: SparseDataFrame does not allow single value data
You can create a normal DataFrame with, e.g., `pandas.DataFrame(0, index=[1, 2, 3], columns=["A", "B", "C"])`.  However, this fails with a SparseDataFrame:

```
>>> x = pandas.SparseDataFrame(0, index=[1, 2, 3], columns=["A", "B", "C"])
Traceback (most recent call last):
  File "<pyshell#97>", line 1, in <module>
    x = pandas.SparseDataFrame(0, index=[1, 2, 3], columns=["A", "B", "C"])
  File "c:\users\brenbarn\documents\python\extensions\pandas\pandas\sparse\frame.py", line 123, in __init__
    NDFrame.__init__(self, mgr)
UnboundLocalError: local variable 'mgr' referenced before assignment
```

It looks like the code in `SparseDataFrame.__init__` is not handling the case where the data is a single value.  It has a bunch of if statements to handle different kinds of data, but falls through without creating `mgr` if none of them are met.

This makes it difficult to create an "empty" SparseDataFrame whose default fill value is something other than `nan`, e.g., `pandas.SparseDataFrame(0, index=[1, 2, 3], columns=["A", "B", "C"], default_fill_value=0)`.  In fact, I would suggest that if a default_fill_value is provided but no data is provided, the SparseDataFrame should be filled with the fill value (not `nan`), but perhaps that warrants a separate issue.
