mean_variance_std.py

# mean_var_std.py
import numpy as np

def calculate(numbers):
    if len(numbers) != 9:
        raise ValueError("List must contain nine numbers.")

    # Convert the list into a 3x3 NumPy array
    matrix = np.array(numbers).reshape(3, 3)

    # Create the dictionary with all required calculations
    calculations = {
        'mean': [matrix.mean(axis=0).tolist(), matrix.mean(axis=1).tolist(), matrix.mean().item()],
        'variance': [matrix.var(axis=0).tolist(), matrix.var(axis=1).tolist(), matrix.var().item()],
        'standard deviation': [matrix.std(axis=0).tolist(), matrix.std(axis=1).tolist(), matrix.std().item()],
        'max': [matrix.max(axis=0).tolist(), matrix.max(axis=1).tolist(), matrix.max().item()],
        'min': [matrix.min(axis=0).tolist(), matrix.min(axis=1).tolist(), matrix.min().item()],
        'sum': [matrix.sum(axis=0).tolist(), matrix.sum(axis=1).tolist(), matrix.sum().item()]
    }

    return calculations