reample, asfreq change columns data types
after resample the data types change to float64, is it possible to keep the input type, uint and uint64 in this example?

```
df=pd.DataFrame([[1,2],[5,6],[2,3]],columns=['a','b'])
df=df.set_index(pd.DatetimeIndex(pd.to_datetime(df.a,unit='s')))
df.b=df.b.astype(np.uint64)
print(df.info())
df2=df.resample('5s')
print(df2.info())
```
===
```
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 3 entries, 1970-01-01 00:00:01 to 1970-01-01 00:00:02
Data columns (total 2 columns):
a    3 non-null int64
b    3 non-null uint64
dtypes: int64(1), uint64(1)
memory usage: 72.0 bytes
None
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 2 entries, 1970-01-01 00:00:00 to 1970-01-01 00:00:05
Freq: 5S
Data columns (total 2 columns):
a    2 non-null float64
b    2 non-null float64
dtypes: float64(2)
memory usage: 48.0 bytes
None
```
