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import pandas as pd
import numpy as np
from datetime import datetime, timedelta

# 生成完整日期序列（排除春节假期）
date_rng = []
dt = datetime(2025,1,1)
while dt <= datetime(2025,6,30):
    if not (dt.month==2 and 13<=dt.day<=17):  # 排除春节假期
        date_rng.append(dt)
    dt += timedelta(days=1)

# 价格生成函数
def generate_price(dt):
    monthly_base = {
        1:(60,65), 2:(62,66), 3:(63,67),
        4:(62,66), 5:(58,63), 6:(56,61)
    }
    base_low, base_high = monthly_base[dt.month]
    daily_adj = np.random.uniform(-0.3, 0.3)
    return f"{max(base_low+daily_adj,55):.1f}-{min(base_high+daily_adj,68):.1f}"

# 生成完整数据集
df = pd.DataFrame({
    "日期": [d.strftime("%Y-%m-%d") for d in date_rng],
    "金属锂价格(万元/吨)": [generate_price(d) for d in date_rng],
    "市场动态": ["模拟数据-"+d.strftime("%m%d") for d in date_rng]
})

# 导出Excel
df.to_excel("2025_metal_lithium_daily_price.xlsx", index=False)