import numpy as np
import numpy as np
calculations = {}
def calculate(list):
try:
len(list)
array_1 = np.array(list)
except len(list)<9:
print(“List must contain nine numbers”)
new_array = array_1.reshape(3,3)
calculations[‘mean’] = [(new_array.mean(axis = 0).tolist()),(new_array.mean(axis = 1).tolist()),(new_array.mean.tolist())]
calculations[‘variance’] = [(new_array.var(axis = 0).tolist()), (new_array.var(axis = 1).tolist()), (new_array.var().tolist())]
calculations[‘standard deviation’] = [(new_array.std(axis = 0).tolist()), (new_array.std(axis = 1).tolist()),(new_array.std().tolist())]
calculations[‘max’] = [(new_array.max(axis = 0).tolist()), (new_array.max(axis = 1).tolist()), (new_array.max().tolist())]
calculations[‘min’] = [(new_array.min(axis = 0).tolist()), (new_array.min(axis = 1).tolist()),(new_array.min().tolist())]
calculations[‘sum’] = [(new_array.sum(axis = 0).tolist()), (new_array.sum(axis = 1).tolist()), (new_array.sum().tolist())]
return calculations