Python 如何将pd.to_timedelta（）转换为time（）对象？

我需要获得

0天08:00:00

到

08:00:00

代码：

输出：

print (df)
   Slot_no  start_time        end_time         location_type  loc_set
0        1    00:01:00 0 days 08:00:00        not considered      NaN
1        2    08:01:00 0 days 10:00:00                  Food      NaN
2        3    10:01:00 0 days 12:00:00      Parks & Outdoors      NaN
3        4    12:01:00 0 days 14:00:00                  Food      NaN
4        5    14:01:00 0 days 18:00:00  Arts & Entertainment      NaN
5        6    18:01:00 0 days 20:00:00      Parks & Outdoors      NaN
6        7    20:01:00 1 days 00:00:00                  Food      NaN

您可以使用：

---

你的问题是什么？你的密码在哪里？

print (df)
   Slot_no  start_time        end_time         location_type  loc_set
0        1    00:01:00 0 days 08:00:00        not considered      NaN
1        2    08:01:00 0 days 10:00:00                  Food      NaN
2        3    10:01:00 0 days 12:00:00      Parks & Outdoors      NaN
3        4    12:01:00 0 days 14:00:00                  Food      NaN
4        5    14:01:00 0 days 18:00:00  Arts & Entertainment      NaN
5        6    18:01:00 0 days 20:00:00      Parks & Outdoors      NaN
6        7    20:01:00 1 days 00:00:00                  Food      NaN

df['end_time_times'] = pd.to_datetime(df['end_time']).dt.time
print (df)
   Slot_no  start_time        end_time         location_type  loc_set  \
0        1    00:01:00 0 days 08:00:00        not considered      NaN   
1        2    08:01:00 0 days 10:00:00                  Food      NaN   
2        3    10:01:00 0 days 12:00:00      Parks & Outdoors      NaN   
3        4    12:01:00 0 days 14:00:00                  Food      NaN   
4        5    14:01:00 0 days 18:00:00  Arts & Entertainment      NaN   
5        6    18:01:00 0 days 20:00:00      Parks & Outdoors      NaN   
6        7    20:01:00 1 days 00:00:00                  Food      NaN   

  end_time_times  
0       08:00:00  
1       10:00:00  
2       12:00:00  
3       14:00:00  
4       18:00:00  
5       20:00:00  
6       00:00:00