Python 如何有效地按日内时间过滤时间序列的时间索引？

我有一个（TimeSeries数据）数据帧，它看起来像这样：

                              A1           A2  ...           Z1            Z2
2019-06-17 00:00:01          NaN          NaN  ...          NaN           NaN
2019-06-17 00:01:59          NaN          NaN  ...          NaN           NaN
2019-06-17 00:02:29          NaN          NaN  ...          NaN           NaN 
                         ...          ...  ...          ...           ...
2020-06-17 23:55:01          NaN          NaN  ...          NaN           NaN 
2020-06-17 23:58:45          NaN          NaN  ...          NaN           NaN
2020-06-17 23:59:59          NaN          NaN  ...          NaN           NaN

问题：

人们需要在白天（00:00:00）进行选择，需要保持灵活性，因为秒数也可以高达59秒

如何在给定的两个时间值（例如15:00:00、24:00:00）之间提取索引 但是： 仅在特定的天数范围内（如周一至周四）

（这就是我如何提取范围VAL:）

timeRangeString=“周一、周四，15:00,24:00”#开始时间==15:00:00
#==>结束时间==23:59:59
#==>start\u dayint==0
#==>end_dayint==3

如何将范围上的索引提取到“范围索引”？

IIUC，以及性能

df.loc[df.index.weekday<4]。时间间隔（'15:00'，'00:00'））

我试过：df.loc[df.index.weekday>=start_dayint&df.index.weekday试过：

df.loc[（df.index.weekday>=start_dayint）&（df.index.weekday）
timeRangesString = "Mon,Thur,15:00,24:00"               #<== the input
rangeIndices     = pd.Index()


# time ranges:
start_time =  time.strptime( timeRangesString.split(",")[0], "%H:%M:%S")#.dt.strftime("%H:%M", '%H:%M:%S')
if timeRangesString.split(",")[1]=="24:00":   
    end_time    = pd.to_datetime("23:59:59", format="%H:%M:%S")
else: 
    end_time  =  time.strptime( timeRangesString.split(",")[1], "%H:%M")#.dt.strftime("%H:%M",' %H:%M:%S')

# day ranges:
start_dayint  =  time.strptime( timeRangesString.split(",")[2], "%a").tm_wday
end_dayint    =  time.strptime( timeRangesString.split(",")[3], "%a").tm_wday

# ==>   start_time   == 15:00:00
# ==>   end_time     == 23:59:59
# ==>   start_dayint == 0
# ==>   end_dayint   == 3

df.loc[df.index.weekday < 4].between_time('15:00', '00:00')