计划一种方法来比较两个数据集的趋势

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

# 假设我们有两个数据集
x = np.array([1, 2, 3, 4, 5]).reshape(-1, 1)
y1 = np.array([2, 3, 5, 6, 8])
y2 = np.array([1, 4, 6, 7, 9])

# 线性回归模型
model1 = LinearRegression().fit(x, y1)
model2 = LinearRegression().fit(x, y2)

# 预测值
y1_pred = model1.predict(x)
y2_pred = model2.predict(x)

# 绘图
plt.scatter(x, y1, color='blue', label='Dataset 1')
plt.plot(x, y1_pred, color='blue', linewidth=2)
plt.scatter(x, y2, color='red', label='Dataset 2')
plt.plot(x, y2_pred, color='red', linewidth=2)
plt.legend()
plt.show()

# 比较斜率
slope1 = model1.coef_[0]
slope2 = model2.coef_[0]
print(f"Slope of Dataset 1: {slope1}")
print(f"Slope of Dataset 2: {slope2}")