我有一个从2016-01-01到2020-12-31的时间序列格式的UV值数据框。
print(df.head(24))
date time uv_index
0 2016-01-01 00:00:00 1.0
1 2016-01-01 01:00:00 1.0
2 2016-01-01 02:00:00 1.0
3 2016-01-01 03:00:00 1.0
4 2016-01-01 04:00:00 1.0
5 2016-01-01 05:00:00 1.0
6 2016-01-01 06:00:00 1.0
7 2016-01-01 07:00:00 1.0
8 2016-01-01 08:00:00 1.0
9 2016-01-01 09:00:00 1.0
10 2016-01-01 10:00:00 1.0
11 2016-01-01 11:00:00 1.0
12 2016-01-01 12:00:00 1.0
13 2016-01-01 13:00:00 1.0
14 2016-01-01 14:00:00 1.0
15 2016-01-01 15:00:00 1.0
16 2016-01-01 16:00:00 1.0
17 2016-01-01 17:00:00 2.0
18 2016-01-01 18:00:00 1.0
19 2016-01-01 19:00:00 1.0
20 2016-01-01 20:00:00 1.0
21 2016-01-01 21:00:00 1.0
22 2016-01-01 22:00:00 1.0
23 2016-01-01 23:00:00 1.0
如何创建一个新的列uv_max，它采用每个日期的最大uv_index值。
print(df1.head(24))
date time uv_index uv_max
0 2016-01-01 00:00:00 1.0 2.0
1 2016-01-01 01:00:00 1.0 2.0
2 2016-01-01 02:00:00 1.0 2.0
3 2016-01-01 03:00:00 1.0 2.0
4 2016-01-01 04:00:00 1.0 2.0
5 2016-01-01 05:00:00 1.0 2.0
6 2016-01-01 06:00:00 1.0 2.0
7 2016-01-01 07:00:00 1.0 2.0
8 2016-01-01 08:00:00 1.0 2.0
9 2016-01-01 09:00:00 1.0 2.0
10 2016-01-01 10:00:00 1.0 2.0
11 2016-01-01 11:00:00 1.0 2.0
12 2016-01-01 12:00:00 1.0 2.0
13 2016-01-01 13:00:00 1.0 2.0
14 2016-01-01 14:00:00 1.0 2.0
15 2016-01-01 15:00:00 1.0 2.0
16 2016-01-01 16:00:00 1.0 2.0
17 2016-01-01 17:00:00 2.0 2.0
18 2016-01-01 18:00:00 1.0 2.0
19 2016-01-01 19:00:00 1.0 2.0
20 2016-01-01 20:00:00 1.0 2.0
21 2016-01-01 21:00:00 1.0 2.0
22 2016-01-01 22:00:00 1.0 2.0
23 2016-01-01 23:00:00 1.0 2.0
usegroupby()+transform():
df['uv_max']=df.groupby('date')['uv_index'].transform('max')