Sqlachemy raises when writing write timedelta64 columns to sqlite.
Maybe we can work around this. At least it should raise informatively.

```
In [24]: df = pd.to_timedelta(Series(['00:00:01', '00:00:03'], name='foo')).to_frame()

In [25]: df
Out[25]: 
       foo
0 00:00:01 
1 00:00:03

[2 rows x 1 columns]

In [26]: df.dtypes
Out[26]: 
foo    timedelta64[ns]
dtype: object

In [27]: df.to_sql('bar', engine)
(...)
StatementError: unsupported operand type(s) for +: 'datetime.datetime' and 'long' (original cause: TypeError: unsupported operand type(s) for +: 'datetime.datetime' and 'long') 'INSERT INTO bar (foo) VALUES (?)' [{'foo': 1000000000L}, {'foo': 3000000000L}]
```

The full traceback is [in this gist](https://gist.github.com/danielballan/11178744).

Using a `sqlite3.Connection` (legacy-style) allows you to write and read.

```
In [32]: conn = sqlite3.connect(':memory:')

In [33]: df.to_sql('bar', conn)

In [37]: pd.read_sql('SELECT * FROM bar', conn, flavor='sqlite')
Out[37]: 
   index         foo
0      0  1000000000
1      1  3000000000
```

The data comes back as `int64` type. There is no clean way around this, no obvious way to tell that these sqlite3 integers are actually timedeltas. We could store timedeltas as strings, like datetimes. But I'm not necessarily in favor of that approach.
