Rolling window with step size
Just a suggestion - extend `rolling` to support a rolling window with a step size, such as R's `rollapply(by=X)`.

#### Code Sample

Pandas - inefficient solution (apply function to every window, then slice to get every second result)
```python
import pandas
ts = pandas.Series(range(0, 40, 2))
ts.rolling(5).apply(max).dropna()[::2]
```

Suggestion:
```python
ts = pandas.Series(range(0, 40, 2))
ts.rolling(window=5, step=2).apply(max).dropna()
```

Inspired by R (see [rollapply](http://svitsrv25.epfl.ch/R-doc/library/zoo/html/rollapply.html) docs):
```r
require(zoo)
TS <- zoo(seq(0, 40, 2))
rollapply(TS, 5, FUN=max, by=2)
```

>  8 12 16 20 24 28 32 36 40 
