Weird behaviour when creating `Series` with datetimes parsed from strings
#### Code Sample, a copy-pastable example if possible

```
x = [u'2016-07-19T00:00:00.000Z',
       u'2016-07-19T01:00:00.000Z',
       u'2016-07-19T02:00:00.000Z',
       u'2016-07-19T03:00:00.000Z',
       u'2016-07-19T04:00:00.000Z',
       u'2016-07-19T05:00:00.000Z',
       u'2016-07-19T06:00:00.000Z',
       u'2016-07-19T07:00:00.000Z',
       u'2016-07-19T08:00:00.000Z',
       u'2016-07-19T09:00:00.000Z',
       u'2016-07-19T10:00:00.000Z',
       u'2016-07-19T11:00:00.000Z',
       u'2016-07-19T12:00:00.000Z',
       u'2016-07-19T13:00:00.000Z',
       u'2016-07-19T14:00:00.000Z',
       u'2016-07-19T15:00:00.000Z',
       u'2016-07-19T16:00:00.000Z',
       u'2016-07-19T17:00:00.000Z',
       u'2016-07-19T18:00:00.000Z',
       u'2016-07-19T19:00:00.000Z',
       u'2016-07-19T20:00:00.000Z',
       u'2016-07-19T21:00:00.000Z',
       u'2016-07-19T22:00:00.000Z',
       u'2016-07-19T23:00:00.000Z']
print pd.Series([dateutil.parser.parse(y) for y in x])
print pd.Series([dateutil.parser.parse(y) for y in (x + x + x)])
```
#### Expected Output

```
0    2016-07-19 00:00:00+00:00
1    2016-07-19 01:00:00+00:00
2    2016-07-19 02:00:00+00:00
3    2016-07-19 03:00:00+00:00
4    2016-07-19 04:00:00+00:00
5    2016-07-19 05:00:00+00:00
6    2016-07-19 06:00:00+00:00
7    2016-07-19 07:00:00+00:00
8    2016-07-19 08:00:00+00:00
9    2016-07-19 09:00:00+00:00
10   2016-07-19 10:00:00+00:00
11   2016-07-19 11:00:00+00:00
12   2016-07-19 12:00:00+00:00
13   2016-07-19 13:00:00+00:00
14   2016-07-19 14:00:00+00:00
15   2016-07-19 15:00:00+00:00
16   2016-07-19 16:00:00+00:00
17   2016-07-19 17:00:00+00:00
18   2016-07-19 18:00:00+00:00
19   2016-07-19 19:00:00+00:00
20   2016-07-19 20:00:00+00:00
21   2016-07-19 21:00:00+00:00
22   2016-07-19 22:00:00+00:00
23   2016-07-19 23:00:00+00:00
dtype: datetime64[ns, tzlocal()]
0    2016-07-19 00:00:00
1    2016-07-19 01:00:00
2    2016-07-19 02:00:00
3    2016-07-19 03:00:00
4    2016-07-19 04:00:00
5    2016-07-19 05:00:00
6    2016-07-19 06:00:00
7    2016-07-19 07:00:00
8    2016-07-19 08:00:00
9    2016-07-19 09:00:00
10   2016-07-19 10:00:00
11   2016-07-19 11:00:00
12   2016-07-19 12:00:00
13   2016-07-19 13:00:00
14   2016-07-19 14:00:00
15   2016-07-19 15:00:00
16   2016-07-19 16:00:00
17   2016-07-19 17:00:00
18   2016-07-19 18:00:00
19   2016-07-19 19:00:00
20   2016-07-19 20:00:00
21   2016-07-19 21:00:00
22   2016-07-19 22:00:00
23   2016-07-19 23:00:00
24   2016-07-19 00:00:00
25   2016-07-19 01:00:00
26   2016-07-19 02:00:00
27   2016-07-19 03:00:00
28   2016-07-19 04:00:00
29   2016-07-19 05:00:00
             ...        
42   2016-07-19 18:00:00
43   2016-07-19 19:00:00
44   2016-07-19 20:00:00
45   2016-07-19 21:00:00
46   2016-07-19 22:00:00
47   2016-07-19 23:00:00
48   2016-07-19 00:00:00
49   2016-07-19 01:00:00
50   2016-07-19 02:00:00
51   2016-07-19 03:00:00
52   2016-07-19 04:00:00
53   2016-07-19 05:00:00
54   2016-07-19 06:00:00
55   2016-07-19 07:00:00
56   2016-07-19 08:00:00
57   2016-07-19 09:00:00
58   2016-07-19 10:00:00
59   2016-07-19 11:00:00
60   2016-07-19 12:00:00
61   2016-07-19 13:00:00
62   2016-07-19 14:00:00
63   2016-07-19 15:00:00
64   2016-07-19 16:00:00
65   2016-07-19 17:00:00
66   2016-07-19 18:00:00
67   2016-07-19 19:00:00
68   2016-07-19 20:00:00
69   2016-07-19 21:00:00
70   2016-07-19 22:00:00
71   2016-07-19 23:00:00
dtype: datetime64[ns, tzlocal()]
```
#### output of `pd.show_versions()`

```
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.10.final.0
python-bits: 64
OS: Darwin
OS-release: 15.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8

pandas: 0.18.1
nose: None
pip: 8.1.1
setuptools: 21.2.1
Cython: None
numpy: 1.11.0
scipy: None
statsmodels: None
xarray: None
IPython: 3.1.0
sphinx: None
patsy: None
dateutil: 2.5.2
pytz: 2016.4
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: 3.6.0
bs4: 4.4.1
html5lib: 0.999
httplib2: 0.9.2
apiclient: 1.5.1
sqlalchemy: None
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
jinja2: 2.7.3
boto: None
pandas_datareader: None
```
