Code Sample, a copy-pastable example if possible
pd.date_range(start='2017-06-01 00:00:00+02:00',
end='2017-08-01 00:00:00+02:00',
freq='15min',
tz='Europe/Berlin')
AssertionError: Inferred time zone not equal to passed time zone
Problem description
The given times are valid times in the Europe/Berlin timezone. However, as can be seen when the tz parameter is not passed, pandas detects them as pytz.FixedOffset(120) and then raises an error because this is not the same as Europe/Berlin.
When giving tz-aware datetimes with different UTC offsets due to a daylight savings change (e.g. 2017-06-01 00:00:00+02:00 and 2017-12-01 00:00:00+01:00), there is a
TypeError: Start and end cannot both be tz-aware with different timezones
Expected Output
DatetimeIndex(['2017-06-01 00:00:00+02:00', '2017-06-01 00:15:00+02:00',
'2017-06-01 00:30:00+02:00', '2017-06-01 00:45:00+02:00',
...
'2017-07-31 23:30:00+02:00', '2017-07-31 23:45:00+02:00'],
dtype='datetime64[ns, Europe/Berlin]', length=6048, freq='15T')
Output of pd.show_versions()
pd.show_versions()
/home/cjk/.conda/lib/python3.6/site-packages/xarray/core/formatting.py:16: FutureWarning: The pandas.tslib module is deprecated and will be removed in a future version.
from pandas.tslib import OutOfBoundsDatetime
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Linux
OS-release: 4.10.0-27-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8
pandas: 0.20.1
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: 0.9.2
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
Comment From: jreback
what you are doing is inherently ambiguous; these timezones are not aliases of each other, rather distinct.
In [32]: pytz.FixedOffset(120) == pytz.timezone('Europe/Berlin')
Out[32]: False
This is not a bug, rather you need to convert the tz.
e.g.
In [27]: pd.date_range(start='2017-06-01 00:00:00+02:00',
...: end='2017-08-01 00:00:00+02:00',
...: freq='15min').tz_convert('Europe/Berlin')
...:
...:
Out[27]:
DatetimeIndex(['2017-06-01 00:00:00+02:00', '2017-06-01 00:15:00+02:00',
'2017-06-01 00:30:00+02:00', '2017-06-01 00:45:00+02:00',
'2017-06-01 01:00:00+02:00', '2017-06-01 01:15:00+02:00',
'2017-06-01 01:30:00+02:00', '2017-06-01 01:45:00+02:00',
'2017-06-01 02:00:00+02:00', '2017-06-01 02:15:00+02:00',
...
'2017-07-31 21:45:00+02:00', '2017-07-31 22:00:00+02:00',
'2017-07-31 22:15:00+02:00', '2017-07-31 22:30:00+02:00',
'2017-07-31 22:45:00+02:00', '2017-07-31 23:00:00+02:00',
'2017-07-31 23:15:00+02:00', '2017-07-31 23:30:00+02:00',
'2017-07-31 23:45:00+02:00', '2017-08-01 00:00:00+02:00'],
dtype='datetime64[ns, Europe/Berlin]', length=5857, freq='15T')