MultiIndex with dateutil tzlocal data corruption
#### Code Sample, a copy-pastable example if possible

```
In [1]: %paste
import datetime
from dateutil.tz import tzlocal, tzutc
import pandas

d = {
    datetime.datetime(2016, 8, 26, 20, 23, tzinfo=tzlocal()): {
        'A': 10481.0,
        'B': 12,
        'C': 'text'
    },
    datetime.datetime(2016, 8, 26, 20, 24, tzinfo=tzlocal()): {
        'A': 10480.5,
        'B': 13,
        'C': 'text'
    }
}

df = pandas.DataFrame(d).T
df2 = df.set_index(['C'], append=True)
## -- End pasted text --

In [2]: df
Out[2]: 
                                 A   B     C
2016-08-26 20:23:00+02:00    10481  12  text
2016-08-26 20:24:00+02:00  10480.5  13  text

In [3]: df2
Out[3]: 
                                      A   B
                          C                
2016-08-26 20:23:00+02:00 text    10481  12
1970-01-01 00:00:00+01:00 text  10480.5  13
```
#### Expected Output

```
In [3]: df2
Out[3]: 
                                      A   B
                          C                
2016-08-26 20:23:00+02:00 text    10481  12
2016-08-26 20:24:00+02:00 text  10480.5  13
```

Note, issue goes away when removing the `tzinfo=tzlocal()`. Or just using `tzinfo=tzutc()`. It can also be reproduced using `MultiIndex()` with tuples instead of `set_index()`.
#### Using pytz works

```
import datetime
import pytz
import tzlocal
import pandas

local_tz = tzlocal.get_localzone()

d = {
    datetime.datetime(2016, 8, 26, 20, 23, tzinfo=pytz.utc).astimezone(local_tz): {
        'A': 10481.0,
        'B': 12,
        'C': 'text'
    },
    datetime.datetime(2016, 8, 26, 20, 24, tzinfo=pytz.utc).astimezone(local_tz): {
        'A': 10480.5,
        'B': 13,
        'C': 'text'
    }
}

df = pandas.DataFrame(d).T
df2 = df.set_index(['C'], append=True)
```
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Linux
OS-release: 4.6.6-300.fc24.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.utf8

pandas: 0.18.0
nose: None
pip: 8.0.2
setuptools: 20.1.1
Cython: 0.23.4
numpy: 1.11.0
scipy: 0.16.1
statsmodels: 0.6.1
xarray: None
IPython: 3.2.1
sphinx: None
patsy: 0.4.1
dateutil: 2.5.2
pytz: 2016.6.1
blosc: None
bottleneck: 0.6.0
tables: 3.2.2
numexpr: 2.6.1
matplotlib: 1.5.2rc2
openpyxl: None
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
jinja2: 2.8
boto: None
