外貌溢价多维度分析（多子图）

def solve():
    import pandas as pd
    import matplotlib.pyplot as plt
    import numpy as np
    
    url = 'https://liangdaima.com/static/data/wooldridge/beauty.csv'
    df = pd.read_csv(url)
    
    fig, axes = plt.subplots(2, 2, figsize=(14, 10))
    sample = df.sample(min(500, len(df)), random_state=42)
    axes[0,0].hist(sample['wage'], bins=20, color='steelblue', edgecolor='black', alpha=0.7)
    axes[0,0].set_title('工资分布')
    axes[0,1].scatter(sample['looks'], sample['wage'], alpha=0.3, color='green')
    axes[0,1].set_title('外貌评分 vs 工资')
    looks_means = df.groupby('belavg')['wage'].mean()
    axes[1,0].bar(['低于平均', '高于平均'], looks_means.values, color=['coral', 'teal'], alpha=0.7)
    axes[1,0].set_title('不同外貌水平平均工资')
    axes[1,1].boxplot([df[df['female']==0]['wage'], df[df['female']==1]['wage']], labels=['男性', '女性'])
    axes[1,1].set_title('性别工资对比')
    for ax in axes.flat:
        ax.grid(alpha=0.3)
    plt.tight_layout()
    plt.show()
    return "可视化代码执行完成"