import numpy as np
def calculate(data):
if len(data) != 9:
raise ValueError("List must contain nine numbers.")
# Convert the input list into a 3x3 Numpy array
matrix = np.array(data).reshape(3, 3)
# Calculate mean, variance, standard deviation, max, min, and sum
result = {
'mean': {
'row': matrix.mean(axis=1).tolist(),
'col': matrix.mean(axis=0).tolist(),
'element': matrix.mean().item()
},
'variance': {
'row': matrix.var(axis=1).tolist(),
'col': matrix.var(axis=0).tolist(),
'element': matrix.var().item()
},
'standard deviation': {
'row': matrix.std(axis=1).tolist(),
'col': matrix.std(axis=0).tolist(),
'element': matrix.std().item()
},
'max': {
'row': matrix.max(axis=1).tolist(),
'col': matrix.max(axis=0).tolist(),
'element': matrix.max().item()
},
'min': {
'row': matrix.min(axis=1).tolist(),
'col': matrix.min(axis=0).tolist(),
'element': matrix.min().item()
},
'sum': {
'row': matrix.sum(axis=1).tolist(),
'col': matrix.sum(axis=0).tolist(),
'element': matrix.sum().item()
}
}
return result
from main import calculate
data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
result = calculate(data)
print(result)
