Failure when constructing a DataFrame from multiple time series.
From [stackoverflow](http://stackoverflow.com/questions/11848578/pandas-messing-up-data-frame).

Constructing a DataFrame from multiple time series fails, all values from the resulting frame are NaN (which is not the case in the individual series).

Code to reproduce: http://pastebin.com/WTsCkKrL

I could reproduce it.

``` python
In [101]: np.__version__
Out[101]: '1.6.1'

In [102]: pandas.__version__
Out[102]: '0.8.2.dev-8cde377'

In [103]: df
Out[103]: 
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 386 entries, 1992-06-05 15:50:11.527680 to 1774-08-13 02:00:15.237103
Data columns:
770000000006    0  non-null values
770000000009    0  non-null values
770000000010    0  non-null values
770000000011    0  non-null values
770000000012    0  non-null values
770000000013    0  non-null values
770000000018    0  non-null values
770000000020    0  non-null values
770000000021    0  non-null values
770000000022    0  non-null values
770000000024    0  non-null values
770000000029    0  non-null values
770000000030    0  non-null values
770000000032    0  non-null values
770000000034    0  non-null values
770000000049    0  non-null values
dtypes: float64(16)
```
