dataframe asfreq modifies the colums dtype
A dataframe like this, volume column is of type int64.

```
print(Gold_2012.head(), "\n")
print(Gold_2012)
                       open    high     low   close  volume
date_time                                                  
2012-01-02 18:01:00  1571.0  1571.0  1569.1  1569.8     351
2012-01-02 18:02:00  1569.8  1570.0  1569.7  1569.8      54
2012-01-02 18:03:00  1570.0  1570.0  1569.1  1569.9     247
2012-01-02 18:04:00  1570.0  1570.0  1569.8  1569.9      55
2012-01-02 18:05:00  1569.8  1569.9  1568.5  1568.5      48 

<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 351367 entries, 2012-01-02 18:01:00 to 2012-12-31 17:15:00
Data columns (total 5 columns):
open      351367  non-null values
high      351367  non-null values
low       351367  non-null values
close     351367  non-null values
volume    351367  non-null values
dtypes: float64(4), int64(1)
```

However, after 
    Gold_2012.asfreq(pd.offsets.Minute())

It becomes:

```
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 524115 entries, 2012-01-02 18:01:00 to 2012-12-31 17:15:00
Freq: T
Data columns (total 5 columns):
open      351367  non-null values
high      351367  non-null values
low       351367  non-null values
close     351367  non-null values
volume    351367  non-null values
dtypes: float64(5)
```

The volume column becomes dtype of float64.

system:

```
Panadas version:  0.11.0
Numpy version:  1.7.1
Matplotlib version:  1.2.1
Python version:  3.3.1 (default, May 12 2013, 21:14:39) 
[GCC 4.2.1 Compatible Apple Clang 4.0 (tags/Apple/clang-418.0.60)]
```
