闻嗅复核：多指标异常差异率综合判断

"____""____""____"

metadata = {
    "____": "____",
    "____": "____",
    "____": "____",
    "____": "____",
    "____": ["____"],
    "____": ["____", "____", "____"],
    "____": ____
}

# 题目描述
"____""____"重点关注"____"正常"____""____"

def solve():
    import pandas as pd
    from pyodide.http import open_url
    from io import StringIO

    BASE_URL = "____"
    df = pd.read_csv(StringIO(open_url(____).read()))

    h1 = df[df['____'] == '____'].iloc[____]
    fy = df[df['____'] == '____'].iloc[____]

    h2_rev = fy['____'] - h1['____']
    h2_cost = fy['____'] - h1['____']
    h2_sell = fy['____'] - h1['____']
    h2_op = fy['____'] - h1['____']
    h2_net = fy['____'] - h1['____']

    h1_gm = (____) / h1['____']
    h2_gm = (____) / h2_rev

    rows = []
    items = [
        (____),
        (____),
        (____),
        (____),
        (____),
        (____),
    ]
    for name, v1, v2 in items:
        rate = round((____) / abs(____), ____)
        flag = '____' if abs(____) > ____ else '____'
        rows.append({'____': name, '____': round(____), '____': round(____),
                     '____': rate, '____': flag})

    return pd.DataFrame(____).to_string()

if __name__ == "____":
    print(solve())