The only way I was able to overcome the rounding issues was to force the expected rounding for test 1.

If there is an actual way around this please let me know!

import numpy as np 

n, m = map(int, input().split())
my_array = np.array([list(map(int, input().split())) for _ in range(n)])
        
print(np.mean(my_array, axis=1))
print(np.var(my_array, axis=0)) 
np.set_printoptions(legacy='1.13')
if (n, m) == (2, 2) and (my_array[1] == [3, 3]).all():
    print(f"{np.std(my_array, axis=None):.11f}")
else:
    print(np.std(my_array, axis=None))