print("{0:.3f}".format(stats.mannwhitneyu(orders[orders['group']=='A']['revenue'], orders[orders['group']=='B']['revenue'])[1]))
print("{0:.3f}".format(orders[orders['group']=='B']['revenue'].mean()/orders[orders['group']=='A']['revenue'].mean()-1))

0.365
0.259


print("{0:.3f}".format(stats.mannwhitneyu(
    orders[np.logical_and(
        orders['group']=='A',
        np.logical_not(orders['userId'].isin(abnormalUsers)))]['revenue'],
    orders[np.logical_and(
        orders['group']=='B',
        np.logical_not(orders['userId'].isin(abnormalUsers)))]['revenue'])[1]))

print("{0:.3f}".format(
    orders[np.logical_and(orders['group']=='B',np.logical_not(orders['userId'].isin(abnormalUsers)))]['revenue'].mean()/
    orders[np.logical_and(
        orders['group']=='A',
        np.logical_not(orders['userId'].isin(abnormalUsers)))]['revenue'].mean() - 1))
0.369
-0.020