这样的输入

 measured_at                  celsius
0 2020-05-19 01:13:40+00:00    15.00
1 2020-05-19 01:14:40+00:00    16.50
1 2020-05-20 02:13:26+00:00    30.00
2 2020-05-20 02:14:57+00:00    15.35
3 2020-05-20 02:15:19+00:00    14.00
4 2020-05-20 12:06:39+00:00    20.00
5 2020-05-21 03:13:07+00:00    15.50
6 2020-05-22 12:09:37+00:00    15.00


df['measured_at'] = pd.to_datetime(df.measured_at)
df1 = df.resample('60T', on='measured_at')['celsius'].mean().dropna().reset_index()

输出显示为此格式

     measured_at    celsius
0 2020-05-19 01:00:00+00:00  15.750000
1 2020-05-20 02:00:00+00:00  19.783333
2 2020-05-20 12:00:00+00:00  20.000000
3 2020-05-21 03:00:00+00:00  15.500000
4 2020-05-22 12:00:00+00:00  15.000000

预期输出为

     measured_at    celsius
0 2020-05-19 01:13:00+00:00  15.750000
1 2020-05-20 02:13:00+00:00  19.783333
2 2020-05-20 12:06:00+00:00  20.000000
3 2020-05-21 03:13:00+00:00  15.500000
4 2020-05-22 12:09:00+00:00  15.000000

我想要的结果像预期的输出意味着有时间2.13，2.14，2.15意味着计算和显示时间的第一个指标时间提供如果任何人有一个解决方案，请分享感谢提前。