astype not converting timedelta and datetime strings
#### Code Sample, a copy-pastable example if possible

```python
>>> s = pd.Series(['0:0:1'])
>>> s.astype('timedelta64[ns]')
WTF timedelta64[ns]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/sergey/projects/pandas/pandas/util/_decorators.py", line 177, in wrapper
    return func(*args, **kwargs)
  File "/home/sergey/projects/pandas/pandas/core/generic.py", line 5182, in astype
    **kwargs)
  File "/home/sergey/projects/pandas/pandas/core/internals/managers.py", line 554, in astype
    return self.apply('astype', dtype=dtype, **kwargs)
  File "/home/sergey/projects/pandas/pandas/core/internals/managers.py", line 421, in apply
    applied = getattr(b, f)(**kwargs)
  File "/home/sergey/projects/pandas/pandas/core/internals/blocks.py", line 564, in astype
    **kwargs)
  File "/home/sergey/projects/pandas/pandas/core/internals/blocks.py", line 655, in _astype
    values = astype_nansafe(values.ravel(), dtype, copy=True)
  File "/home/sergey/projects/pandas/pandas/core/dtypes/cast.py", line 717, in astype_nansafe
    return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
  File "pandas/_libs/lib.pyx", line 455, in pandas._libs.lib.astype_intsafe
    util.set_value_at_unsafe(result, i, v)
  File "pandas/_libs/tslibs/util.pxd", line 145, in pandas._libs.tslibs.util.set_value_at_unsafe
    assign_value_1d(arr, i, value)
ValueError: Could not convert object to NumPy timedelta
```
Same with datetime.
#### Expected Output
```python
>>> s.astype('timedelta64[ns]')
0   00:00:01
dtype: timedelta64[ns]

```
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: 114f4153400cd917058a69f79660d18076d9609a
python: 3.6.6.final.0
python-bits: 64
OS: Linux
OS-release: 4.13.0-46-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.0.dev0+365.g114f41534.dirty
pytest: 3.6.2
pip: 10.0.1
setuptools: 39.2.0
Cython: 0.28.3
numpy: 1.14.5
scipy: 1.1.0
pyarrow: 0.9.0
xarray: 0.10.7
IPython: 6.4.0
sphinx: 1.7.5
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.5
feather: 0.4.0
matplotlib: 2.2.2
openpyxl: 2.5.4
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.5
lxml: 4.2.2
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.8
pymysql: 0.8.1
psycopg2: None
jinja2: 2.10
s3fs: 0.1.5
fastparquet: 0.1.5
pandas_gbq: None
pandas_datareader: None
gcsfs: 0.1.0
</details>
