datetime + timedelta64: TypeError: ufunc add cannot use operands with types dtype('O') and dtype('<m8[ns]')
#### Adding a couple milliseconds to datetime

```python
fmt = '%Y-%m-%d %H:%M:%S %z'
datelist = ['2017-02-24 18:21:49 -0800', '2017-02-24 18:21:49 -0800', '2017-02-24 18:21:49 -0700']
dateseries = pd.Series(datelist)
tmptime = dateseries .apply(datetime.strptime, args=(fmt,))
```
since different time zones, tmptime won't be converted to dtype datetime64 and instead stay as datetime.datetime

```python
addms = pd.Series([1, 2, 3])
addoffset = addms * timedelta(microseconds = 10000) # series of dtype timedelta64
tmptime + addoffset 
# TypeError: ufunc add cannot use operands with types dtype('O') and dtype('<m8[ns]')
```

#### Problem description

I want to add a couple milliseconds to a datetime object in pandas. The datatime object is not automatically converted into datetime64 when holding different time zones (and to_datetime() doesn't understand z in the fmt string). This creates the case where one pandas series is of type datetime while the time difference is of type timedelta64. Addition is not possible between these two types. It also does not seem possible to have pandas hold a timedelta (automatically converted to timedelta64). A workaround would be to add milliseconds in timedelta that is in a list (below)

#### Expected Output

```python
addoffset2 = [i * timedelta(microseconds = 10000) for i in [1,2,3]] # list of type datetime.timedelta
tmptime + addoffset2
```
output
```out
0    2017-02-24 18:21:49.010000-08:00
1    2017-02-24 18:21:49.020000-08:00
2    2017-02-24 18:21:49.030000-07:00
dtype: object
```

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.20.1
pytest: None
pip: 9.0.1
setuptools: 27.2.0
Cython: None
numpy: 1.12.1
scipy: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: 1.1.9
pymysql: None
psycopg2: 2.7.1 (dt dec pq3 ext lo64)
jinja2: None
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
