Using loc with assignment and multiple columns fails
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
df = pd.DataFrame({'a': range(4), 'b': range(4,8)})
df.loc[df.a==2, ['a', 'b']] = df.loc[df.a==2, ['b', 'a']]
print df
```
produces:
```
   a  b
0  0  4
1  1  5
2  2  6
3  3  7
```
#### Problem description

This should interchange the value for column and b for when `a == 2`. Right now it silently does nothing. 


#### Expected Output
```
   a  b
0  0  4
1  1  5
2  6  2
3  3  7
```
#### Output of ``pd.show_versions()``

<details>
# Paste the output here pd.show_versions() here
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Darwin
OS-release: 16.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.19.2
nose: 1.3.6
pip: 8.1.2
setuptools: 35.0.1
Cython: 0.24
numpy: 1.12.1
scipy: 0.18.1
statsmodels: 0.8.0rc1
xarray: None
IPython: 5.2.2
sphinx: None
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.3
openpyxl: None
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.4.0
html5lib: 0.9999999
httplib2: 0.9.2
apiclient: None
sqlalchemy: 1.0.11
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
jinja2: 2.9.5
boto: 2.39.0
pandas_datareader: None
</details>
