DataFrame.to_xarray produces FutureWarning for DatetimeTZ data
```python
In [16]: df = pd.DataFrame({"A": pd.date_range('2000', periods=12, tz='US/Central')})

In [17]: df.to_xarray()
/Users/taugspurger/Envs/pandas-dev/lib/python3.7/site-packages/xarray/core/dataset.py:3111: FutureWarning: Converting timezone-aware DatetimeArray to timezone-naive ndarray with 'datetime64[ns]' dtype. In the future, this will return an ndarray with 'object' dtype where each element is a 'pandas.Timestamp' with the correct 'tz'.
        To accept the future behavior, pass 'dtype=object'.
        To keep the old behavior, pass 'dtype="datetime64[ns]"'.
  data = np.asarray(series).reshape(shape)
Out[17]:
<xarray.Dataset>
Dimensions:  (index: 12)
Coordinates:
  * index    (index) int64 0 1 2 3 4 5 6 7 8 9 10 11
Data variables:
    A        (index) datetime64[ns] 2000-01-01T06:00:00 ... 2000-01-12T06:00:00
```

@shoyer thoughts on how to resolve this? We can continue dropping the timezone and passing datetime64[ns], break API and return an object-dtype array of timestamps, or add a parameter so that the user can control this.