'Construct a Classifier computing quintile labels on ``self``.
Every non-NaN data point the output is labelled with a value of either
0, 1, 2, or 3, 4, corresonding to quintiles over each row.  NaN data
points are labelled with -1.
If ``mask`` is supplied, ignore data points in locations for which
``mask`` produces False, and emit a label of -1 at those locations.
Parameters
mask : zipline.pipeline.Filter, optional
Mask of values to ignore when computing quintiles.
Returns
quintiles : zipline.pipeline.classifiers.Quantiles
A Classifier producing integer labels ranging from 0 to 4.'

@expect_types(mask=(Filter, NotSpecifiedType))
def quintiles(self, mask=NotSpecified):

    return self.quantiles(bins=5, mask=mask)
