按错误类型聚类分析

def solve():
    from pyodide.http import open_url
    from io import StringIO
    request_logs_csv = open_url("https://data.zuihe.com/dbd/ms-shop/state_06/request_logs.csv").read()
    import pandas as pd
    from io import StringIO
    logs = pd.read_csv(StringIO(request_logs_csv))
    def classify_error(code):
        if code < 400: return 'success'
        if code == 400: return '400_bad_request'
        if code == 401: return '401_unauthorized'
        if code == 403: return '403_forbidden'
        if code == 404: return '404_not_found'
        if code == 429: return '429_too_many'
        if code >= 500: return '5xx_server_error'
        return f'{code}_other'
    logs['error_class'] = logs['status_code'].apply(classify_error)
    print("错误类型分布:")
    dist = logs.groupby('error_class').size().sort_values(ascending=False)
    for cls, cnt in dist.items():
        pct = cnt / len(logs) * 100
        print(f"  {cls}: {cnt} ({pct:.1f}%)")
    print("按路径×错误类型:")
    cross = logs[logs['error_class']!='success'].groupby(['path','error_class']).size()
    print(cross.to_string())