wrong addition between Series of type datetime64 and timedelta when tz is set and different from UTC

[sdementen]

It seems there is an issue when adding a timedelta to a Series of type datetime64[ns, some tz]. There seems to be an issue with the offset/DST.

Code Sample, a copy-pastable example if possible

import pandas

sr = pandas.Series(pandas.DatetimeIndex(["2016-11-03 16:00:00+01:00", "2016-10-25 17:00:00+02:00"]).tz_localize("UTC").tz_convert(tz="Europe/Brussels"))
print(sr)
print(sr + pandas.to_timedelta(0, unit='h'))

Actual Output

0   2016-11-03 16:00:00+01:00
1   2016-10-25 17:00:00+02:00
dtype: datetime64[ns, Europe/Brussels]
0   2016-11-03 16:00:00+01:00
1   2016-10-25 16:00:00+02:00
dtype: datetime64[ns, Europe/Brussels]

Expected Output

0   2016-11-03 16:00:00+01:00
1   2016-10-25 17:00:00+02:00
dtype: datetime64[ns, Europe/Brussels]
0   2016-11-03 16:00:00+01:00
1   2016-10-25 17:00:00+02:00
dtype: datetime64[ns, Europe/Brussels]

output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.5.2.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.1
nose: None
pip: 8.1.2
setuptools: 23.0.0
Cython: None
numpy: 1.11.0
scipy: 0.17.1
statsmodels: None
xarray: None
IPython: 4.2.0
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.1
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: None
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: None
html5lib: None
httplib2: 0.9.2
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext)
jinja2: 2.8
boto: None
pandas_datareader: None

[jreback]

dupe of #13905

[sdementen]

I have the impression it is not exactly the same bug. It appears specifically when

• DST is active for the given date (there is no bug for 2016-11-03 16:00:00+01:00 as DST is not active for this time). If I adapt the example to match the case from DatetimeIndex + TimeDelta gives wrong results when timezone is set #13905, I have no issue:

import pandas
sr =  pandas.Series(pandas.DatetimeIndex(['2016-06-28 05:30', '2016-06-28 05:31'], type='datetime64[ns, America/Chicago]'))
print(sr)
print((sr + pandas.to_timedelta(0, unit='h')))

gives

0   2016-06-28 05:30:00-05:00
1   2016-06-28 05:31:00-05:00
dtype: datetime64[ns, America/Chicago]
0   2016-06-28 05:30:00-05:00
1   2016-06-28 05:31:00-05:00
dtype: datetime64[ns, America/Chicago]

• adding the timedelta to a Series (and not an index). If we use a DateTimeIndex instead of a Series

sr =  pandas.DatetimeIndex(["2016-12-03 16:00:00", "2016-10-25 17:00:00"], dtype='datetime64[ns, Europe/Brussels]')
print(sr)
print((sr + pandas.to_timedelta(0, unit='h')))

it works as expected

DatetimeIndex(['2016-12-03 16:00:00+01:00', '2016-10-25 17:00:00+02:00'], dtype='datetime64[ns, Europe/Brussels]', freq=None)
DatetimeIndex(['2016-12-03 16:00:00+01:00', '2016-10-25 17:00:00+02:00'], dtype='datetime64[ns, Europe/Brussels]', freq=None)