python - 如果在时间范围内，则更改列的值

Question

如果一列的值落在以下时间(17:00 到 23:00)之间，我将尝试修改它们，否则，它们必须保持相同的值。这是我的代码:

lclstd['Response KWH/hh (per half hour) ']=lclstd['KWH/hh (per half hour) '].astype(float)

从日期时间列中提取时间

lclstd['Time']=pd.to_datetime(lclstd['DateTime']).dt.strftime ('%H:%M:%S')

仅在 17:00 至 23:00 的高峰时段分配响应

lclstd.loc[(lclstd['Time'] == '17:00:00') | (lclstd['Time'] == '17:30:00') | (lclstd['Time'] == '18:00:00') | (lclstd['Time'] == '18:30:00') | (lclstd['Time'] == '19:00:00') | (lclstd['Time'] == '19:30:00') | (lclstd['Time'] == '20:00:00') | (lclstd['Time'] == '20:30:00') | (lclstd['Time'] == '21:00:00') | (lclstd['Time'] == '21:30:00') | (lclstd['Time'] == '22:00:00') | (lclstd['Time'] == '22:30:00') | (lclstd['Time'] == '23:00:00') , 'Response KWH/hh (per half hour) '] = 0.9*lclstd['Response KWH/hh (per half hour) ']

但我收到以下错误

ValueError: cannot reindex from a duplicate axis

Answer 1

pd.Series.dt.time返回datetime.time对象。所以你可以通过 pd.Series.between 进行比较创建蒙版。然后喂给loc :

from datetime import time

time1, time2 = time(17), time(23)                # 17:00, 23:00

df['Time'] = pd.to_datetime(df['Time'])          # convert to datetime if necessary
mask = df['Time'].dt.time.between(time1, time2)  # inclusive of boundaries by default

df.loc[mask, 'Response KWH/hh (per half hour) '] *= 0.9