import numpy as np

def calculate_covariance_matrix(vectors):
    # 补全代码
    fist_array = np.array(vectors)
    n = fist_array.shape[1]
    means = np.mean(fist_array, axis=1, keepdims=True)
    center = fist_array - means
    return (np.dot(center, center.T)/(n-1)).tolist()


# 主程序
if __name__ == "__main__":
    # 输入
    ndarrayA = input()

    # 处理输入
    import ast
    A = ast.literal_eval(ndarrayA)

    # 调用函数计算
    output = calculate_covariance_matrix(A)
    
    # 输出结果
    print(output)