[Feature Request] Pass array of timezones to pandas.Series.tz_convert
This feature request spurs from this StackOverflow question: http://stackoverflow.com/questions/35659927/how-can-i-get-the-timezone-adjusted-hour-for-each-row-in-a-pandas-dataframe-when

The relevant portions are copied here.

Given a DataFrame like:

```
#        publication_timestamp     timezone
# uuid
#0    2015-07-28 00:10:05.852   US/Central
#1    2015-10-03 00:17:43.000   US/Eastern
#2    2015-08-20 01:15:52.693   US/Eastern
#3    2015-09-09 00:02:03.083   US/Pacific
#4    2015-12-08 00:02:41.390  US/Mountain
```

I would like to output a DataFrame like this:

```
#        publication_timestamp     timezone  hour  adjusted_hour time_of_day
# uuid
#0    2015-07-28 00:10:05.852   US/Central     0             19     evening
#1    2015-10-03 00:17:43.000   US/Eastern     0             20     evening
#2    2015-08-20 01:15:52.693   US/Eastern     1             21     evening
#3    2015-09-09 00:02:03.083   US/Pacific     0             17     evening
#4    2015-12-08 00:02:41.390  US/Mountain     0             17     evening
```

I would like to be able to pass `tz_convert` a column of timezones and have each row using a different timezone. 

**I understand that you can't (shouldn't?) combine multiple dtypes in the same column**, HOWEVER - I would like to just use this as an intermediate step in getting the timezone adjusted hour (i.e. time of day) for each row.
#### output of `pd.show_versions()`

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Darwin
OS-release: 15.0.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.17.1
nose: 1.3.7
pip: 8.0.3
setuptools: 19.4
Cython: None
numpy: 1.10.4
scipy: 0.17.0
statsmodels: 0.6.1
IPython: 4.1.1
sphinx: 1.3.5
patsy: 0.4.1
dateutil: 2.2
pytz: 2015.7
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.1
openpyxl: 2.2.0-b1
xlrd: 0.9.4
xlwt: None
xlsxwriter: None
lxml: 3.5.0
bs4: 4.4.1
html5lib: None
httplib2: 0.9.2
apiclient: 1.4.2
sqlalchemy: 1.0.11
pymysql: None
psycopg2: None
Jinja2: 2.8
```
