如何计算每行的标准差？

import numpy as np

# 示例数据，每行代表一个样本的数据
data = np.array([[1, 2, 3],
                 [4, 5, 6],
                 [7, 8, 9]])

# 计算每行的平均值
row_mean = np.mean(data, axis=1)

# 计算每个数据点与平均值的差值
diff = data - row_mean.reshape(-1, 1)

# 计算方差并取平均
variance = np.mean(diff**2, axis=1)

# 计算每行的标准差
std_dev = np.sqrt(variance)

# 打印结果
for i in range(len(std_dev)):
    print("第{}行的标准差：{}".format(i+1, std_dev[i]))