BUG: resample doesn't work for non-numeric types
After discussion on the ML it was decided the below function _should_ work in pandas.

It fails on the current master (0.11.0.dev-308beb1) with 32bit Python 2.7 on windows

``` python
def test_resample_nonnumeric():
    import numpy as np
    import pandas as pd
    dates = pd.date_range('01-Jan-2014','05-Jan-2014', freq='D')
    series = pd.TimeSeries(['a','b','c','d','e'], index=dates)
    resampled_series = series[[0,1,3,4]].resample('D', fill_method='ffill')
    assert (resampled_series.index == dates).all()
    assert (resampled_series.values == np.asarray(['a','b','b','d','e'], dtype=object)).all()
```

https://groups.google.com/forum/?fromgroups=#!topic/pydata/NFA10wTVNu8

addtl example (related), how doing weird things:

```
In [30]: df = pd.DataFrame({
'Buyer': 'Carl Mark Carl Joe Joe Carl'.split(),
'Quantity': [1,3,5,8,9,3],
'Date' : [
    DT.datetime(2013,9,1,13,0),
    DT.datetime(2013,9,1,13,5),
    DT.datetime(2013,10,1,20,0),
    DT.datetime(2013,10,3,10,0),
    DT.datetime(2013,12,2,12,0),                                      
    DT.datetime(2013,12,2,14,0),
    ]}).set_index(['Date'])

In [31]: df
Out[31]: 
                    Buyer  Quantity
Date                               
2013-09-01 13:00:00  Carl         1
2013-09-01 13:05:00  Mark         3
2013-10-01 20:00:00  Carl         5
2013-10-03 10:00:00   Joe         8
2013-12-02 12:00:00   Joe         9
2013-12-02 14:00:00  Carl         3


In [33]: df['Quantity'].resample('10D',how=sum)
Out[33]: 
Date
2013-09-01 13:00:00     4.000000e+00
2013-09-11 13:00:00              NaN
2013-09-21 13:00:00              NaN
2013-10-01 13:00:00     1.300000e+01
2013-10-11 13:00:00              NaN
2013-10-21 13:00:00              NaN
2013-10-31 13:00:00              NaN
2013-11-10 13:00:00              NaN
2013-11-20 13:00:00              NaN
2013-11-30 13:00:00     1.200000e+01
2013-12-10 13:00:00    7.637868e-317
Freq: 10D, dtype: float64
```
