DataFrame.to_xarray() is sorting dimensional coordinates
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np

rd = np.zeros((4,4), dtype=np.float64)
lag = np.arange(4)[::-1]
# lag = np.random.randn(4) 
lev = np.arange(4)

iterables = [lag, lev]
index = pd.MultiIndex.from_product(iterables, names=['lag','lev'])
solution = pd.DataFrame(data=rd.reshape(rd.size, 1),index=index)
solution.columns = ['tmp']

solution.to_xarray()

```
Output:
```
<xarray.Dataset>
Dimensions:  (lag: 4, lev: 4)
Coordinates:
  * lag      (lag) int64 0 1 2 3
  * lev      (lev) int64 0 1 2 3
Data variables:
    tmp      (lag, lev) float64 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...
```
#### Problem description

The dimensions of the generated `xarray.Dataset` is sorted in ascending order for `lag`.
This is true for any entry (like the commented out `np.random.randn(4)` line)

#### Expected Output

```
<xarray.Dataset>
Dimensions:  (lag: 4, lev: 4)
Coordinates:
  * lag      (lag) int64 3 2 1 0
  * lev      (lev) int64 0 1 2 3
Data variables:
    tmp      (lag, lev) float64 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...
```
#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.5.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-327.22.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.19.1
nose: None
pip: 9.0.1
setuptools: 30.2.0
Cython: None
numpy: 1.11.2
scipy: 0.18.1
statsmodels: None
xarray: 0.8.2
IPython: 5.1.0
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None
</details>