python回归分析代码
时间: 2023-10-14 17:30:36 浏览: 26
以下是一个简单的线性回归分析的Python代码示例:
```python
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
# 读取数据
data = pd.read_csv('data.csv')
# 准备数据
X = data.iloc[:, :-1].values
y = data.iloc[:, 1].values
# 将数据集分为训练集和测试集
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
# 训练模型
regressor = LinearRegression()
regressor.fit(X_train, y_train)
# 预测测试集结果
y_pred = regressor.predict(X_test)
# 可视化训练集结果
plt.scatter(X_train, y_train, color='red')
plt.plot(X_train, regressor.predict(X_train), color='blue')
plt.title('Salary vs Experience (Training set)')
plt.xlabel('Years of Experience')
plt.ylabel('Salary')
plt.show()
# 可视化测试集结果
plt.scatter(X_test, y_test, color='red')
plt.plot(X_train, regressor.predict(X_train), color='blue')
plt.title('Salary vs Experience (Test set)')
plt.xlabel('Years of Experience')
plt.ylabel('Salary')
plt.show()
```
这里假设你有一个名为"data.csv"的数据集,其中包含两列数据:一列是经验年数,另一列是薪水。你可以将其替换为你自己的数据集,然后运行这个代码进行分析。