将每日数据分配给分钟数据Pandas Dataframe

import pandas as pd

# 创建空的分钟级别的Dataframe
df_minute = pd.DataFrame(columns=['时间', '数据'])

# 遍历每日数据
for index, row in df_daily.iterrows():
    date = row['日期']
    data = row['数据']
    
    # 将每日数据按照分钟级别进行分配
    for minute in range(0, 1440):
        time = pd.Timestamp(date) + pd.Timedelta(minutes=minute)
        df_minute = df_minute.append({'时间': time, '数据': data}, ignore_index=True)

# 计算每分钟的平均值
df_minute['平均值'] = df_minute.groupby(pd.Grouper(key='时间', freq='1Min'))['数据'].transform('mean')

# 计算每分钟的最大值
df_minute['最大值'] = df_minute.groupby(pd.Grouper(key='时间', freq='1Min'))['数据'].transform('max')

# 计算每分钟的最小值
df_minute['最小值'] = df_minute.groupby(pd.Grouper(key='时间', freq='1Min'))['数据'].transform('min')