我有以下数据集
dVal eVal
0 2015-01-01 00:00:00.000 3.622833
1 2015-01-01 01:00:00.000 3.501333
2 2015-01-01 02:00:00.000 3.469167
3 2015-01-01 03:00:00.000 3.436333
4 2015-01-01 04:00:00.000 3.428000
5 2015-01-01 05:00:00.000 3.400667
6 2015-01-01 06:00:00.000 3.405667
7 2015-01-01 07:00:00.000 3.401500
8 2015-01-01 08:00:00.000 3.404333
9 2015-01-01 09:00:00.000 3.424833
10 2015-01-01 10:00:00.000 3.489500
11 2015-01-01 11:00:00.000 3.521000
12 2015-01-01 12:00:00.000 3.527833
13 2015-01-01 13:00:00.000 3.523500
14 2015-01-01 14:00:00.000 3.511667
15 2015-01-01 15:00:00.000 3.602500
16 2015-01-01 16:00:00.000 3.657667
17 2015-01-01 17:00:00.000 3.616667
18 2015-01-01 18:00:00.000 3.534500
19 2015-01-01 19:00:00.000 3.529167
20 2015-01-01 20:00:00.000 3.548167
21 2015-01-01 21:00:00.000 3.565500
22 2015-01-01 22:00:00.000 3.539833
23 2015-01-01 23:00:00.000 3.485667
24 2015-01-02 00:00:00.000 3.493167
.........
.........
我想在白天做一个列评估的平均值。
如果将dval列转换为datetime,则执行第一步。
time['dVal'] = pd.to_datetime(time['dVal'])
接下来,我将datetime列设置为索引
time.index = time['dVal']
最后我每天都数平均数
me = time.resample('D').mean()
平均数算错了。
dVal eVal
2015-01-01 4.014973 --> The correct mean of the first day is 3.5
2015-01-02 4.006548
2015-01-03 4.010406
2015-01-04 4.034531
