检测Pandas Dataframe的所有列中的异常值

import pandas as pd
import numpy as np

data = {'A': [1, 2, 3, 4, 5],
        'B': [10, 20, 30, 40, 50],
        'C': [100, 200, 300, 400, 500]}
df = pd.DataFrame(data)

def detect_outliers(df):
    outliers = []
    for column in df.columns:
        # 计算列的均值和标准差
        mean = np.mean(df[column])
        std = np.std(df[column])
        # 定义异常值的阈值（例如，超过均值的3倍标准差）
        threshold = 3 * std
        # 检测异常值
        column_outliers = df[(df[column] < mean - threshold) | (df[column] > mean + threshold)]
        outliers.append(column_outliers)
    return outliers

outliers = detect_outliers(df)
for i, column_outliers in enumerate(outliers):
    if not column_outliers.empty:
        print("列 {} 中的异常值：".format(df.columns[i]))
        print(column_outliers)