Pandas Append with two DateTimeIndex returns Index and not DateTimeIndex

In 0.19.1 appending a DateTimeIndex to another DateTimeIndex where they have different time zones now returns an Index object. In 0.18.1 it would return a DateTimeIndex with a UTC time zone.

In 0.19.1 (and in 0.18.1) if the two DateTimeIndex have the same time zone a DateTimeIndex is returned. I believe the behavior in 0.18.1 of returning a DateTimeIndex with time zone UTC should be the correct behavior.

--- Example of the problem ---

import pandas as pd

df1 = pd.DataFrame({'a': [1, 2, 3]}, index=pd.date_range('1990-02-01 09:00:00', periods=3, freq='1min', tz='America/New_York'))
df2 = pd.DataFrame({'a': [4, 5, 6]}, index=pd.date_range('1990-02-01 08:03:00', periods=3, freq='1min', tz='America/Chicago'))

print(df1.index.tzinfo)  # America/New_York
print(df2.index.tzinfo)  # America/Chicago

result = df1.index.append(df2.index)

print(type(new_index))
print(type(result))

>> pandas 0.18.1 returns <class 'pandas.tseries.index.DatetimeIndex'>
>> pandas 0.19.1 returns <class 'pandas.indexes.base.Index'>

Comment From: jreback

Appending different timezones and coercing to UTC loses information. It is up to the user to explicitly coerce to the same timezone if you don't want this behavior. Having mixed timezones within a single object is only supported with boxed objects, hence the object dtype.

This what fixed in #13360 / xref issue was #7795

In [16]: result.tolist()
Out[16]: 
[Timestamp('1990-02-01 09:00:00-0500', tz='America/New_York', freq='T'),
 Timestamp('1990-02-01 09:01:00-0500', tz='America/New_York', freq='T'),
 Timestamp('1990-02-01 09:02:00-0500', tz='America/New_York', freq='T'),
 Timestamp('1990-02-01 08:03:00-0600', tz='America/Chicago', freq='T'),
 Timestamp('1990-02-01 08:04:00-0600', tz='America/Chicago', freq='T'),
 Timestamp('1990-02-01 08:05:00-0600', tz='America/Chicago', freq='T')]

from above.