def calculate_covariance_matrix(vectors):
    mean = [sum(j for j in i) / len(vectors[0]) for i in vectors]
    return [
        [
            (
                sum(
                    (x - mean[i]) * (y - mean[j])
                    for x, y in zip(vectors[i], vectors[j])
                )
                / (len(vectors[i]) - 1)
            )
            for j in range(len(vectors))
        ]
        for i in range(len(vectors))
    ]
    # 补全代码


# 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)