DatetimeIndex bug when adding offset to tz-aware
Migrated from pydata mailing list

Let me begin by saying -- I have worked out a way around the problem using .shift(). But I still thought I would mention what I ran into and see if it's worthy of attention/fixing. 

I create a DatetimeIndex with a timezone:

```
In [29]: dates = pd.DatetimeIndex(start='2012-11-01',periods = 10, freq = 'D', tz='US/Pacific')
In [30]: dates
Out[30]: 
<class 'pandas.tseries.index.DatetimeIndex'>
[2012-11-01 00:00:00, ..., 2012-11-10 00:00:00]
Length: 10, Freq: D, Timezone: US/Pacific
```

Great! Now I want to have all of my timestamps be at 5am. So I try: 

```
dates + pd.offsets.Hour(5)
```

And get: 

```
<class 'pandas.tseries.index.DatetimeIndex'>
[2012-11-01 12:00:00, ..., 2012-11-10 13:00:00]
Length: 10, Freq: None, Timezone: US/Pacific 
```

Hmm. Suddenly its 12 noon -- not 5am. It looks like pandas is trying to do some UTC to US/Pacific conversion -- even though I've already specified my timezone. 

This just surprised me and has the feeling of a bug. 

 Again, I solved it when I remembered I could do .shift()

```
In [32]: dates.shift(5,freq='H')
Out[32]: 
<class 'pandas.tseries.index.DatetimeIndex'>
[2012-11-01 05:00:00, ..., 2012-11-10 05:00:00]
Length: 10, Freq: None, Timezone: US/Pacific
```
