Averaging along row looses timestamp information
data

```
import numpy as np
import pandas

data1 = np.arange(24)
data2 = 24 - np.arange(24)

dates = pandas.DateRange(start=datetime.datetime(2005,1,1),
periods=24, offset=pandas.datetools.MonthEnd())
DF = pandas.DataFrame({'data1':data1, 'data2':data2}, index=dates)

ann_range = pandas.DateRange(start=datetime.datetime(2005,1,1,0),
end=datetime.datetime(2007,1,1),offset=12*pandas.datetools.MonthEnd())

DF.groupby(clim_range.asof).mean() 

```

Now averaging data1 & data2 for each row

```
df.groupby(lambda x: x.month).mean() 
```

After this, the timestamp is lost:
An enumerated key (1-12) is returned. 

One would need to have now a series with frequency monthly.

Reference:
https://groups.google.com/group/pystatsmodels/browse_thread/thread/9b1b9a3152c3709a/0b01d056cf9491ff?hl=en%EF%BF%BDb01d056cf9491ff
