Python 如何将时间数据转换为数值？

我有一个数据帧

输出

：

          dates       min       max       wh
0     2005-09-06  07:41:18  21:59:57 14:18:39
1     2005-09-12  14:49:22  14:49:22 00:00:00
2     2005-09-19  11:08:56  11:24:05 00:15:09
3     2005-09-21  21:19:21  21:20:15 00:00:54
4     2005-09-22  19:41:52  19:41:52 00:00:00
5     2005-10-13  11:22:07  21:05:41 09:43:34
6     2005-11-22  11:53:12  21:21:22 09:28:10
7     2005-11-23  00:07:01  14:08:50 14:01:49
8     2005-11-30  13:42:48  23:59:19 10:16:31
9     2005-12-01  00:05:16  10:24:12 10:18:56
10    2005-12-21  17:38:43  19:26:03 01:47:20
11    2005-12-22  09:20:07  11:25:40 02:05:33
12    2006-01-23  07:46:20  08:01:52 00:15:32
13    2006-04-27  16:27:54  19:29:52 03:01:58
14    2006-05-11  12:48:34  23:10:44 10:22:10
15    2006-05-15  10:14:59  22:28:12 12:13:13
16    2006-05-16  01:14:07  23:55:51 22:41:44
17    2006-05-17  01:12:45  23:57:56 22:45:11
18    2006-05-18  02:42:08  21:48:49 19:06:41

我想要每月每天的平均工作时间（显示

wh

）列

out['dates'] = pd.to_datetime(out['dates'])
out['month']= pd.PeriodIndex(out.dates, freq='M')
out2=out.groupby('month')['wh'].mean().reset_index(name='wh2')

到目前为止，我使用了这个，但是

wh

中的值不是数字数据，所以我无法建立平均值。如何转换整列

wh

构建平均值

我的

wh

是由以下人员完成的：

 df = pd.read_csv("Testordner2/"+i, parse_dates=True)
 df['new_time'] = pd.to_datetime(df['new_time'])
 df['dates']= df['new_time'].dt.date
 df['time'] = df['new_time'].dt.time
 out = df.groupby(df['dates']).agg({'time': ['min', 'max']}) \
                                 .stack(level=0).droplevel(1)
 out['min_as_time_format'] = pd.to_datetime(out['min'],    format="%H:%M:%S")
 out['max_as_time_format'] = pd.to_datetime(out['max'], format="%H:%M:%S")
 out['wh'] = out['max_as_time_format'] - out['min_as_time_format']
 out['wh'].astype(str).str[-18:-10]

---

一种可能的解决方案是将时间增量转换为本机格式，聚合

mean

，然后转换回时间增量：

out['dates'] = pd.to_datetime(out['dates'])
out['month']= pd.PeriodIndex(out.dates, freq='M')

out['wh'] = pd.to_timedelta(out['wh']).astype(np.int64)
out2=pd.to_timedelta(out.groupby('month')['wh'].mean()).reset_index(name='wh2')

print (out2)
     month             wh2
0  2005-09 02:54:56.400000
1  2005-10        09:43:34
2  2005-11        11:15:30
3  2005-12 04:43:56.333333
4  2006-01        00:15:32
5  2006-04        03:01:58
6  2006-05 17:25:47.800000