Stripped timedelta[s] series represented as timedelta[ns]
```
In [2]: s = pd.Series(range(61)).astype('timedelta64[s]')

In [3]: s.tail(1)
Out[3]: 
60   00:01:00
dtype: timedelta64[s]

In [4]: str(s).splitlines()[-2]
Out[4]: '60   00:00:00.000000'
```

... because the snipped representation interprets the content of the series as nanoseconds rather than milliseconds. The same happens with `timedelta[ms]` and probably any other resolution (if there are).

```
In [5]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit: 404819358e90da57c8025a259ab58cd75426069f
python: 3.4.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.3.0-1-amd64
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: it_IT.utf8

pandas: 0.18.0rc1+35.g4048193
nose: 1.3.6
pip: 1.5.6
setuptools: 20.1.1
Cython: 0.23.2
numpy: 1.10.0.post2
scipy: 0.16.0
statsmodels: 0.8.0.dev0+755fa81
xarray: None
IPython: 4.1.1
sphinx: 1.3.1
patsy: 0.3.0-dev
dateutil: 2.4.2
pytz: 2015.6
blosc: None
bottleneck: None
tables: 3.2.2
numexpr: 2.4.3
matplotlib: 1.5.dev1
openpyxl: None
xlrd: 0.9.4
xlwt: None
xlsxwriter: 0.7.3
lxml: None
bs4: 4.4.0
html5lib: 0.999
httplib2: 0.9.1
apiclient: None
sqlalchemy: 1.0.11
pymysql: None
psycopg2: None
jinja2: 2.8
```
