BUG: DatetimeIndex.astype doesn't fully handle tz aware dtypes

[jschendel]

Code Sample, a copy-pastable example if possible

Setup:

In [2]: dti_naive = pd.date_range('2017-01-01', periods=4)
   ...: dti_east = pd.date_range('2017-01-01', periods=4, tz='US/Eastern')
   ...: dti_west = pd.date_range('2017-01-01', periods=4, tz='US/Pacific')
   ...:

Attempting to convert between aware always converts to UTC and becomes naive:

In [3]: dti_west.astype(dti_east.dtype)
Out[3]:
DatetimeIndex(['2017-01-01 08:00:00', '2017-01-02 08:00:00',
               '2017-01-03 08:00:00', '2017-01-04 08:00:00'],
              dtype='datetime64[ns]', freq='D')

Converting naive to aware does nothing:

In [4]: dti_naive.astype(dti_east.dtype)
Out[4]: DatetimeIndex(['2017-01-01', '2017-01-02', '2017-01-03', '2017-01-04'], dtype='datetime64[ns]', freq='D')

Converting aware to naive appears to work:

In [5]: dti_west.astype(dti_naive.dtype)
Out[5]:
DatetimeIndex(['2017-01-01 08:00:00', '2017-01-02 08:00:00',
               '2017-01-03 08:00:00', '2017-01-04 08:00:00'],
              dtype='datetime64[ns]', freq='D')

Expected Output

For [3]:

In [3]: dti_west.astype(dti_east.dtype)
Out[3]:
DatetimeIndex(['2017-01-01 03:00:00-05:00', '2017-01-02 03:00:00-05:00',
               '2017-01-03 03:00:00-05:00', '2017-01-04 03:00:00-05:00'],
              dtype='datetime64[ns, US/Eastern]', freq='D')

For [4]:

In [4]: dti_naive.astype(dti_east.dtype)
Out[4]:
DatetimeIndex(['2017-01-01 00:00:00-05:00', '2017-01-02 00:00:00-05:00',
               '2017-01-03 00:00:00-05:00', '2017-01-04 00:00:00-05:00'],
              dtype='datetime64[ns, US/Eastern]', freq='D')

Output of pd.show_versions()

INSTALLED VERSIONS

commit: a18d725
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0.dev0+433.ga18d725
pytest: 3.1.2
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.13.1
scipy: 0.19.1
pyarrow: 0.6.0
xarray: 0.9.6
IPython: 6.1.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.2
numexpr: 2.6.2
feather: 0.4.0
matplotlib: 2.0.2
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 0.9.8
lxml: 3.8.0
bs4: None
html5lib: 0.999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: 0.1.0
pandas_gbq: None
pandas_datareader: None