In [2]: df = pd.DataFrame(np.random.randn(1000,1000))In [3]: df[df >0.9]= pd.np.nanIn [4]:%timeit df.isnull().any().any()100 loops, best of 3:14.7 ms per loopIn [5]:%timeit df.isnull().values.sum()100 loops, best of 3:2.15 ms per loopIn [6]:%timeit df.isnull().sum().sum()100 loops, best of 3:18 ms per loopIn [7]:%timeit df.isnull().values.any()1000 loops, best of 3:948 µs per loop