Python -向for循环生成的子图添加残差

import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression

# 生成一些示例数据
np.random.seed(0)
X = np.random.rand(100, 1)
y = 2 + 3 * X + np.random.randn(100, 1)

# 创建模型并拟合数据
model = LinearRegression()
model.fit(X, y)

# 预测值
y_pred = model.predict(X)

# 计算残差
residuals = y - y_pred

# 创建子图
fig, axes = plt.subplots(1, 2, figsize=(12, 5))

# 绘制原始数据和拟合线
axes[0].scatter(X, y, color='blue', label='Data')
axes[0].plot(X, y_pred, color='red', label='Fit')
axes[0].set_title('Original Data and Fit')
axes[0].legend()

# 绘制残差图
axes[1].scatter(y_pred, residuals, color='green')
axes[1].axhline(y=0, color='black', linestyle='--')
axes[1].set_title('Residuals Plot')
axes[1].set_xlabel('Predicted Values')
axes[1].set_ylabel('Residuals')

plt.tight_layout()
plt.show()