A small, complete example of the issue

When you try to add a list of timedelta to a column that is datetime the behavior changes if the tzinfo is coming from datetime.tz.tzlocal(). In the example below I make two columns of timestamps, on with tz.tzlocal() and the other tz.tzutc() and then try to add a list of timedelta to it. The tzutc() ones behave as expected but the ones with tzloca() only the first row does the addition properly and for the rest the addition is done to unix epoch of 0!

# Your code here
import datetime
from dateutil import tz
import pandas as pd
dates1 = [datetime.datetime(2013, 9, 20,13,00, tzinfo=tz.tzlocal()) + datetime.timedelta(minutes=100*i) for i in range(10)]
dates2 = [datetime.datetime(2013, 9, 20,13,00, tzinfo=tz.tzutc()) + datetime.timedelta(minutes=100*i) for i in range(10)]
df = pd.DataFrame({"start1": dates1, "start2": dates2})
delta = [datetime.timedelta(seconds=x) for x in range(10)]
df['end1'] = df['start1'] + delta
df['end2'] = df['start2'] + delta
df

Expected Output

                 start1                    start2  \

0 2013-09-20 13:00:00-07:00 2013-09-20 13:00:00+00:00
1 2013-09-20 14:40:00-07:00 2013-09-20 14:40:00+00:00
2 2013-09-20 16:20:00-07:00 2013-09-20 16:20:00+00:00
3 2013-09-20 18:00:00-07:00 2013-09-20 18:00:00+00:00
4 2013-09-20 19:40:00-07:00 2013-09-20 19:40:00+00:00
5 2013-09-20 21:20:00-07:00 2013-09-20 21:20:00+00:00
6 2013-09-20 23:00:00-07:00 2013-09-20 23:00:00+00:00
7 2013-09-21 00:40:00-07:00 2013-09-21 00:40:00+00:00
8 2013-09-21 02:20:00-07:00 2013-09-21 02:20:00+00:00
9 2013-09-21 04:00:00-07:00 2013-09-21 04:00:00+00:00 

                   end1                      end2

0 2013-09-20 13:00:00-07:00 2013-09-20 13:00:00+00:00
1 2013-09-20 13:00:01-07:00 2013-09-20 14:40:01+00:00
2 2013-09-20 13:00:02-07:00 2013-09-20 16:20:02+00:00
3 2013-09-20 13:00:03-07:00 2013-09-20 18:00:03+00:00
4 2013-09-20 13:00:04-07:00 2013-09-20 19:40:04+00:00
5 2013-09-20 13:00:05-07:00 2013-09-20 21:20:05+00:00
6 2013-09-20 13:00:06-07:00 2013-09-20 23:00:06+00:00
7 2013-09-20 13:00:07-07:00 2013-09-21 00:40:07+00:00
8 2013-09-20 13:00:08-07:00 2013-09-21 02:20:08+00:00
9 2013-09-20 13:00:09-07:00 2013-09-21 04:00:09+00:00

Output of pd.show_versions()

# Paste the output here ## INSTALLED VERSIONS commit: None python: 2.7.11.final.0 python-bits: 64 OS: Linux OS-release: 4.7.4-100.fc23.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.utf8 pandas: 0.18.1 nose: 1.3.7 pip: 8.1.2 setuptools: 18.0.1 Cython: 0.23.4 numpy: 1.11.1 scipy: 0.17.1 statsmodels: 0.6.1 xarray: None IPython: 4.1.1 sphinx: 1.2.3 patsy: 0.4.1 dateutil: 2.5.3 pytz: 2016.6.1 blosc: None bottleneck: 0.6.0 tables: None numexpr: 2.4.6 matplotlib: 1.5.1 openpyxl: 1.8.6 xlrd: None xlwt: None xlsxwriter: None lxml: 3.4.4 bs4: None html5lib: None httplib2: None apiclient: None sqlalchemy: 1.0.12 pymysql: None psycopg2: 2.6.1 (dt dec pq3 ext lo64) jinja2: 2.8 boto: 2.41.0 pandas_datareader: None

Comment From: jreback

fixed by #13583, in 0.19.0

In [1]: pd.__version__
Out[1]: '0.19.0'

In [2]: import datetime
   ...: from dateutil import tz
   ...: import pandas as pd
   ...: dates1 = [datetime.datetime(2013, 9, 20,13,00, tzinfo=tz.tzlocal()) + datetime.timedelta(minutes=100*i) for i in range(10)]
   ...: dates2 = [datetime.datetime(2013, 9, 20,13,00, tzinfo=tz.tzutc()) + datetime.timedelta(minutes=100*i) for i in range(10)]
   ...: df = pd.DataFrame({"start1": dates1, "start2": dates2})
   ...: delta = [datetime.timedelta(seconds=x) for x in range(10)]
   ...: df['end1'] = df['start1'] + delta
   ...: df['end2'] = df['start2'] + delta
   ...: df
   ...: 
Out[2]: 
                     start1                    start2                      end1                      end2
0 2013-09-20 13:00:00-04:00 2013-09-20 13:00:00+00:00 2013-09-20 13:00:00-04:00 2013-09-20 13:00:00+00:00
1 2013-09-20 14:40:00-04:00 2013-09-20 14:40:00+00:00 2013-09-20 14:40:01-04:00 2013-09-20 14:40:01+00:00
2 2013-09-20 16:20:00-04:00 2013-09-20 16:20:00+00:00 2013-09-20 16:20:02-04:00 2013-09-20 16:20:02+00:00
3 2013-09-20 18:00:00-04:00 2013-09-20 18:00:00+00:00 2013-09-20 18:00:03-04:00 2013-09-20 18:00:03+00:00
4 2013-09-20 19:40:00-04:00 2013-09-20 19:40:00+00:00 2013-09-20 19:40:04-04:00 2013-09-20 19:40:04+00:00
5 2013-09-20 21:20:00-04:00 2013-09-20 21:20:00+00:00 2013-09-20 21:20:05-04:00 2013-09-20 21:20:05+00:00
6 2013-09-20 23:00:00-04:00 2013-09-20 23:00:00+00:00 2013-09-20 23:00:06-04:00 2013-09-20 23:00:06+00:00
7 2013-09-21 00:40:00-04:00 2013-09-21 00:40:00+00:00 2013-09-21 00:40:07-04:00 2013-09-21 00:40:07+00:00
8 2013-09-21 02:20:00-04:00 2013-09-21 02:20:00+00:00 2013-09-21 02:20:08-04:00 2013-09-21 02:20:08+00:00
9 2013-09-21 04:00:00-04:00 2013-09-21 04:00:00+00:00 2013-09-21 04:00:09-04:00 2013-09-21 04:00:09+00:00