我有一个数据帧，看起来像：
column
2015-01-01 00:00:00 27.38
2015-01-01 01:00:00 23.37
2015-01-01 02:00:00 19.33
2015-01-01 03:00:00 17.66
2015-01-01 04:00:00 17.53
2015-01-01 05:00:00 18.07
2015-01-01 06:00:00 25.23
2015-01-01 07:00:00 26.80
2015-01-01 08:00:00 26.97
2015-01-01 09:00:00 26.29
以此类推，从 2015-01-01 00：00 到 2017-12-31 23：00 每小时
我想对此进行重新采样，以便我取"夜间时间"的平均值和"白天时间"的平均值。我将晚上 18：00 到 07：00 和白天定义为 07：00 到 18：00。从而产生类似
column
2015-01-01 07:00:00 x (This would be the mean of the values from 2015-01-01 00:00:00 to 2015-01-01 07:00:00)
2015-01-01 18:00:00 x (This would be the mean of the values from 2015-01-01 07:00:00 to 2015-01-01 18:00:00)
2015-01-02 07:00:00 x (This would be the mean of the values from 2015-01-01 18:00:00 to 2015-01-02 07:00:00)
2015-01-02 18:00:00 x (This would be the mean of the values from 2015-01-02 07:00:00 to 2015-01-02 18:00:00)
2015-01-03 07:00:00 x (This would be the mean of the values from 2015-01-02 18:00:00 to 2015-01-03 07:00:00)
2015-01-03 18:00:00 x (This would be the mean of the values from 2015-01-03 07:00:00 to 2015-01-03 18:00:00)
我希望清楚我在问什么。如果我要解释什么，请告诉我。
一个简单的解决方法如下：
df[0] = df[0].apply(lambda x: x.split()[0]+' day' if int(x[-8:-6])<=7 else x.split()[0]+' night')
df.groupby(0)[1].mean()
基本上，我将hh:mm:ss的时间替换为day或night。这将使我可以轻松地对它们进行分组并执行所需的任何操作。