Incorrect resampling due to DST
related #5172

Given this DataFrame, with an index containing the moment when DST changes (October 27th in the case of the "Europe/Paris" timezone):

```
index = pandas.date_range('2013-09-30', '2013-11-02', freq = '30Min', tz = 'UTC').tz_convert('Europe/Paris')
column_a = pandas.np.random.random(index.size)
column_b = pandas.np.random.random(index.size)
df = pandas.DataFrame({ "a": column_a, "b": column_b }, index = index)
```

Let's say I want to find the "min" and "max" values for each month:

```
df.resample("MS", how = { "a": "min", "b": "max" })
```

Here's the incorrect result:

```
                                  a         b
2013-09-01 00:00:00+02:00  0.015856  0.979541
2013-10-01 00:00:00+02:00  0.002039  0.999960
2013-10-31 23:00:00+01:00       NaN       NaN
```

Same problem with a "W-MON" frequency:

```
                                  a         b
2013-09-30 00:00:00+02:00  0.015856  0.979541
2013-10-07 00:00:00+02:00  0.007961  0.999734
2013-10-14 00:00:00+02:00  0.002614  0.993354
2013-10-21 00:00:00+02:00  0.005655  0.999960
2013-10-27 23:00:00+01:00       NaN       NaN
2013-11-03 23:00:00+01:00       NaN       NaN
```

Whereas it works fine with a "D" frequency.

```
                                  a         b
...
2013-10-26 00:00:00+02:00  0.004645  0.983281
2013-10-27 00:00:00+02:00  0.030151  0.986827
2013-10-28 00:00:00+01:00  0.015891  0.981455
2013-10-29 00:00:00+01:00  0.024176  0.999306
...
```

Should I resample only the "a" column, it also works fine:

```
df["a"].resample("MS", how = "min")
```

```
2013-09-01 00:00:00+02:00    0.015856
2013-10-01 00:00:00+02:00    0.002039
2013-11-01 00:00:00+01:00    0.000747
Freq: MS, dtype: float64
```

Tested with latest pandas from GIT master.
