BUG: to_datetime with utc=True for Series

[albertvillanova]

Code Sample, a copy-pastable example if possible

In [2]: ts = 1.4884427244831782e+18

In [3]: pd.to_datetime(ts, utc=True)
Out[3]: Timestamp('2017-03-02 08:18:44.483178240+0000', tz='UTC')

In [4]: pd.to_datetime([ts], utc=True)
Out[4]: DatetimeIndex(['2017-03-02 08:18:44.483178240+00:00'], dtype='datetime64[ns, UTC]', freq=None)

In [5]: pd.to_datetime(pd.Series([ts]), utc=True)
Out[5]: 
0   2017-03-02 08:18:44.483178240
dtype: datetime64[ns]

Problem description

The argument utc=True in function to_datetime is not working when passing a Series, differently from other case, e.g. when passing a list or a scalar Unix timestamp.

Expected Output

The expected output is the same as the one given by

In [6]: pd.to_datetime(pd.Series([ts])).dt.tz_localize('UTC')
Out[6]: 
0   2017-03-02 08:18:44.483178240+00:00
dtype: datetime64[ns, UTC]

Another example: tz_convert

It is straightforward to convert to another time zone from a Unix timestamp or list:

In [7]: pd.to_datetime(ts, utc=True).tz_convert('Europe/Paris')
Out[7]: Timestamp('2017-03-02 09:18:44.483178240+0100', tz='Europe/Paris')

In [8]: pd.to_datetime([ts], utc=True).tz_convert('Europe/Paris')
Out[8]: DatetimeIndex(['2017-03-02 09:18:44.483178240+01:00'], dtype='datetime64[ns, Europe/Paris]', freq=None)

whereas for a Series:

In [9]: pd.to_datetime(pd.Series([ts])).dt.tz_localize('UTC').dt.tz_convert('Europe/Paris')
Out[9]: 
0   2017-03-02 09:18:44.483178240+01:00
dtype: datetime64[ns, Europe/Paris]

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.5.2.final.0 python-bits: 64 OS: Linux OS-release: 3.13.0-113-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: ca_ES.UTF-8 LOCALE: ca_ES.UTF-8

pandas: 0.19.2
nose: 1.3.7
pip: 8.1.2
setuptools: 27.2.0.post20161106
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.4.6
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.1.0
tables: 3.2.3.1
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.42.0
pandas_datareader: 0.2.1

[jorisvandenbossche]

@albertvillanova Thanks for the report! This is a duplicate of #6415
PRs welcome!