工资分布核密度估计（统计图表）

def solve():
    import pandas as pd
    import matplotlib.pyplot as plt
    import numpy as np
    
    url = 'https://liangdaima.com/static/data/wooldridge/wage1.csv'
    df = pd.read_csv(url)
    
    from scipy.stats import gaussian_kde
    plt.figure(figsize=(10,6))
    kde = gaussian_kde(df['wage'])
    x_range = np.linspace(df['wage'].min(), df['wage'].max(), 100)
    plt.plot(x_range, kde(x_range), color='blue', linewidth=2)
    plt.fill_between(x_range, kde(x_range), alpha=0.3, color='blue')
    plt.hist(df['wage'], bins=20, density=True, alpha=0.3, color='gray')
    plt.title('工资核密度估计', fontsize=14)
    plt.xlabel('工资', fontsize=12)
    plt.ylabel('密度', fontsize=12)
    plt.grid(alpha=0.3)
    plt.tight_layout()
    plt.show()
    return "可视化代码执行完成"