存货估测：多年历史数据回归参数估计

"____""____""____"

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

"____""____""____"

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

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

    x = df['____'].values
    y = df['____'].values

    coeffs = np.polyfit(____)
    b, a = round(____), round(____)

    y_hat = np.polyval(____)
    ss_res = np.sum((____) ** ____)
    ss_tot = np.sum((y - y.mean()) ** ____)
    r2 = round(____ - ss_res / ss_tot, ____)

    df['____'] = y_hat.round(____)
    df['____'] = (____).round(____)

    header = f"____"
    return header + df[['____', '____', '____', '____']].to_string()

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