使用Pandas中数据帧的最后一列分别回归每一列

import pandas as pd
from sklearn.linear_model import LinearRegression

data = pd.read_csv('data.csv')  # 替换为你的数据集路径
df = pd.DataFrame(data)

def regression(df):
    X = df.iloc[:, :-1]  # 所有列除了最后一列作为自变量
    y = df.iloc[:, -1]  # 最后一列作为因变量
    model = LinearRegression()
    model.fit(X, y)
    return model.coef_, model.intercept_

results = {}
for column in df.columns:
    df_temp = df[[column, df.columns[-1]]].dropna()  # 选择当前列和最后一列的非空行
    if len(df_temp) > 0:
        coef, intercept = regression(df_temp)
        results[column] = {'coef': coef, 'intercept': intercept}

for column, result in results.items():
    print(f"回归结果 - 列名: {column}")
    print(f"回归系数: {result['coef']}")
    print(f"截距: {result['intercept']}")
    print()