Subset a model "y" dataframe
    Args:
        query: operates on y, or aux if present
        subset: takes a dataframe or index thereof and subsets to that
        dropna: means drop missing outcomes
        return: top k (count) or p (proportion) if specified
        p_of: specifies what the proportion is relative to
            'notnull' means proportion is relative to labeled count
            'true' means proportion is relative to positive count
            'all' means proportion is relative to total count

def y_subset(y, query=None, aux=None, subset=None, dropna=False, outcome='true',
             k=None, p=None, ascending=False, score='score', p_of='notnull'):
    """
    Subset a model "y" dataframe
    Args:
        query: operates on y, or aux if present
        subset: takes a dataframe or index thereof and subsets to that
        dropna: means drop missing outcomes
        return: top k (count) or p (proportion) if specified
        p_of: specifies what the proportion is relative to
            'notnull' means proportion is relative to labeled count
            'true' means proportion is relative to positive count
            'all' means proportion is relative to total count
    """
    if query is not None:
        if aux is None:
            y = y.query(query)
        else:
            s = aux.ix[y.index]
            if len(s) != len(y):
                logging.warning('y not a subset of aux')
            y = y.ix[s.query(query).index]

    if subset is not None:
        if hasattr(subset, 'index'):
            subset = subset.index
        y = y.ix[y.index.intersection(subset)]

    if dropna:
        y = y.dropna(subset=[outcome])

    if k is not None and p is not None:
        raise ValueError("Cannot specify both k and p")
    elif k is not None:
        k = k
    elif p is not None:
        if p_of == 'notnull':
            k = int(p*y[outcome].notnull().sum())
        elif p_of == 'true':
            k = int(p*y[outcome].sum())
        elif p_of == 'all':
            k = int(p*len(y))
        else:
            raise ValueError('Invalid value for p_of: %s' % p_of)
    else:
        k = None

    if k is not None:
        y = y.sort_values(score, ascending=ascending).head(k)

    return y