从列表中删除异常值/XY散点

import numpy as np

def remove_outliers_zscore(data, threshold=3):
    mean = np.mean(data)
    std = np.std(data)
    z_scores = [(y - mean) / std for y in data]
    return [data[i] for i in range(len(data)) if np.abs(z_scores[i]) < threshold]

# 示例数据
data = [1, 2, 2, 2, 3, 1, 2, 3, 4, 100]
cleaned_data = remove_outliers_zscore(data)
print(cleaned_data)

def remove_outliers_iqr(data):
    Q1 = np.percentile(data, 25)
    Q3 = np.percentile(data, 75)
    IQR = Q3 - Q1
    lower_bound = Q1 - 1.5 * IQR
    upper_bound = Q3 + 1.5 * IQR
    return [x for x in data if lower_bound <= x <= upper_bound]

# 示例数据
data = [1, 2, 2, 2, 3, 1, 2, 3, 4, 100]
cleaned_data = remove_outliers_iqr(data)
print(cleaned_data)

import matplotlib.pyplot as plt

data = [1, 2, 2, 2, 3, 1, 2, 3, 4, 100]
plt.boxplot(data)
plt.show()