rolling_corr() doesn't handle nan well
rolling_corr() produces a nan result for any window in which either input has a nan value. There is no dropna (or similar) parameter to rolling_corr() to alter this behavior. Contrast with corr(), which dops nans by default. Obviously the user could dropna() on the inputs before invoking rolling_corr(), but it would be convenient to be able to handle it within the method either by deafult (as in corr) or by parameter. 

For example:

> > > import pandas, numpy
> > > df = pandas.DataFrame({'a': numpy.random.random(20), 'b': numpy.random.random(20)})
> > > df['a'][12] = numpy.nan

>>>  df.a.corr(df.b)
0.067541528061417624

> > >  pandas.rolling_corr(df.a, df.b, window=5)
> > > 0          NaN
> > > 1          NaN
> > > 2          NaN
> > > 3          NaN
> > > 4    -0.391790
> > > 5    -0.550723
> > > 6    -0.131031
> > > 7     0.292896
> > > 8     0.056880
> > > 9     0.440123
> > > 10    0.120214
> > > 11   -0.475006
> > > 12         NaN
> > > 13         NaN
> > > 14         NaN
> > > 15         NaN
> > > 16         NaN
> > > 17    0.476328
> > > 18    0.517736
> > > 19    0.886145
