如何使用 pandas 跨列替换时间戳

Question

df = pd.DataFrame({
 'subject_id':[1,1,2,2],
 'time_1':['2173/04/11 12:35:00','2173/04/12 12:50:00','2173/04/11 12:59:00','2173/04/12 13:14:00'],
 'time_2':['2173/04/12 16:35:00','2173/04/13 18:50:00','2173/04/13 22:59:00','2173/04/21 17:14:00'],
  'val' :[5,5,40,40],
  'iid' :[12,12,12,12]   
 })
df['time_1'] = pd.to_datetime(df['time_1'])
df['time_2'] = pd.to_datetime(df['time_2'])
df['day'] = df['time_1'].dt.day

目前我的数据框如下所示

我想将time_1 列中的时间戳替换为00:00:00，将time_2 列替换为23:59:00

这是我尝试过的，但它不起作用

df.groupby(df['subject_id'])['time_1'].apply(lambda x: pd.datetime.strftime(x, "%H:%M:%S") == "00:00:00")   #approach 1

df.groupby(df['subject_id'])['time_1'].apply(lambda x: pd.pd.Timestamp(hour = '00', second = '00')) #approach 2

我希望我的输出数据框如下所示

Answer 1

如果所有日期时间在同一列中都有 00:00:00 时间，则我不显示它。

使用Series.dt.floor 或Series.str.normalize 删除时间，第二次添加DateOffset：

df['time_1'] = pd.to_datetime(df['time_1']).dt.floor('d')
#alternative
#df['time_1'] = pd.to_datetime(df['time_1']).dt.normalize()
df['time_2']=pd.to_datetime(df['time_2']).dt.floor('d') + pd.DateOffset(hours=23, minutes=59)
df['day'] = df['time_1'].dt.day

print (df)
   subject_id     time_1              time_2  val  iid  day
0           1 2173-04-11 2173-04-12 23:59:00    5   12   11
1           1 2173-04-12 2173-04-13 23:59:00    5   12   12
2           2 2173-04-11 2173-04-13 23:59:00   40   12   11
3           2 2173-04-12 2173-04-21 23:59:00   40   12   12