python 用3σ法则检验x变量是否存在异常值，记录异常值的索引，然后剔除x,y值的索引对应的元素函数代码

好的，请输入以下代码：

import numpy as np

def detect_outliers(data):
    mean = np.mean(data)
    std = np.std(data)
    threshold = 3 * std
    
    outlier_indices = []
    for i in range(len(data)):
        if abs(data[i] - mean) > threshold:
            outlier_indices.append(i)
    
    return outlier_indices

def remove_outliers(x, y, outlier_indices):
    x_cleaned = np.delete(x, outlier_indices, axis=0)
    y_cleaned = np.delete(y, outlier_indices, axis=0)
    
    return x_cleaned, y_cleaned

# example usage
x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 100])
y = np.array([10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000])

outlier_indices = detect_outliers(x)

print("Outlier indices:", outlier_indices)

x_cleaned, y_cleaned = remove_outliers(x, y, outlier_indices)

print("x_cleaned:", x_cleaned)
print("y_cleaned:", y_cleaned)

这段代码可以使用3σ法则检验变量x是否存在异常值，并记录异常值的索引。然后利用该索引对应的元素剔除x，y的索引对应的元素。这样可以得到去除异常值的新x和y。