如何在Python中向hh：mm：ss格式添加整数（秒）？

Question

我在python中有以下数据框，我试图通过将'Duration'（以秒为单位）添加到'start_time'来计算列'New time'

Serial  start_date     start_time     Duration(seconds)  New time
    A   5/22/2017       10:37:24        216 
    A   5/22/2017       10:37:26        213 
    A   5/22/2017       10:37:29         3  
    A   5/22/2017       10:39:55         60 
    A   5/22/2017       10:51:50        380 
    A   5/22/2017       10:51:57        339 

我想在start_time中添加持续时间。 持续时间以秒为单位。 '新时间'预计为hh：mm：ss格式。

我试图在论坛中寻找类似的查询，但无法解决这个问题。

以下是信息

data.info()

start_date         13661 non-null object
start_time         13661 non-null object
Duration           13661 non-null int64

我尝试使用datetime从论坛中的类似问题中获取提示

data.newtime = data.start_time + datetime.timedelta(data.Duration)

当我执行此操作时收到以下错误：TypeError：timedelta days组件：系列的不支持类型

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-95-fdfac1490ba5> in <module>()
----> 1 data.newtime = data.start_time + datetime.timedelta(data.Duration)

TypeError: unsupported type for timedelta days component: Series

不确定如何去做。 python新手。

帮助赞赏TIA

Answer 1

您可以使用to_timedelta ，输出也是timedelta ：

df['New time'] = pd.to_timedelta(df['start_time']) + 
                 pd.to_timedelta(df['Duration(seconds)'], unit='s')
print (df)
  Serial start_date start_time  Duration(seconds) New time
0      A  5/22/2017   10:37:24                216 10:41:00
1      A  5/22/2017   10:37:26                213 10:40:59
2      A  5/22/2017   10:37:29                  3 10:37:32
3      A  5/22/2017   10:39:55                 60 10:40:55
4      A  5/22/2017   10:51:50                380 10:58:10
5      A  5/22/2017   10:51:57                339 10:57:36

但是如果秒数更多，则输出会发生变化，因为还有几天：

print (df)
  Serial start_date start_time  Duration(seconds)
0      A  5/22/2017   10:37:24                216
1      A  5/22/2017   10:37:26             213000
2      A  5/22/2017   10:37:29                  3
3      A  5/22/2017   10:39:55                 60
4      A  5/22/2017   10:51:50                380
5      A  5/22/2017   10:51:57                339

df['New time'] = pd.to_timedelta(df['start_time']) + 
                 pd.to_timedelta(df['Duration(seconds)'], unit='s')
print (df)
  Serial start_date start_time  Duration(seconds)        New time
0      A  5/22/2017   10:37:24                216 0 days 10:41:00
1      A  5/22/2017   10:37:26             213000 2 days 21:47:26
2      A  5/22/2017   10:37:29                  3 0 days 10:37:32
3      A  5/22/2017   10:39:55                 60 0 days 10:40:55
4      A  5/22/2017   10:51:50                380 0 days 10:58:10
5      A  5/22/2017   10:51:57                339 0 days 10:57:36

---

也是posible添加日期时间：

df['New date'] = pd.to_datetime(df['start_date']) + \
                 pd.to_timedelta(df['start_time']) +  \
                 pd.to_timedelta(df['Duration(seconds)'], unit='s')
print (df)
  Serial start_date start_time  Duration(seconds)            New date
0      A  5/22/2017   10:37:24                216 2017-05-22 10:41:00
1      A  5/22/2017   10:37:26                213 2017-05-22 10:40:59
2      A  5/22/2017   10:37:29                  3 2017-05-22 10:37:32
3      A  5/22/2017   10:39:55                 60 2017-05-22 10:40:55
4      A  5/22/2017   10:51:50                380 2017-05-22 10:58:10
5      A  5/22/2017   10:51:57                339 2017-05-22 10:57:36

---

df['New date'] = pd.to_datetime(df['start_date']) + \
                 pd.to_timedelta(df['start_time']) +  \
                 pd.to_timedelta(df['Duration(seconds)'], unit='s')
print (df)
  Serial start_date start_time  Duration(seconds)            New date
0      A  5/22/2017   10:37:24                216 2017-05-22 10:41:00
1      A  5/22/2017   10:37:26             213000 2017-05-24 21:47:26
2      A  5/22/2017   10:37:29                  3 2017-05-22 10:37:32
3      A  5/22/2017   10:39:55                 60 2017-05-22 10:40:55
4      A  5/22/2017   10:51:50                380 2017-05-22 10:58:10
5      A  5/22/2017   10:51:57                339 2017-05-22 10:57:36

---

如果需要将timedelta转换为HH:MM:SS格式的string HH:MM:SS和丢失的days （如果存在）：

df['New time'] = pd.to_timedelta(df['start_time']) + 
                 pd.to_timedelta(df['Duration(seconds)'], unit='s')
df['New time'] = pd.to_datetime(df['New time']).dt.strftime('%H:%M:%S')
print (df)
  Serial start_date start_time  Duration(seconds)  New time
0      A  5/22/2017   10:37:24                216  10:41:00
1      A  5/22/2017   10:37:26             213000  21:47:26
2      A  5/22/2017   10:37:29                  3  10:37:32
3      A  5/22/2017   10:39:55                 60  10:40:55
4      A  5/22/2017   10:51:50                380  10:58:10
5      A  5/22/2017   10:51:57                339  10:57:36

Answer 2

这是一个可以帮助您自己解决问题的片段：

from datetime import datetime, timedelta

my_date = datetime.strptime('5/22/2017 10:37:24', '%m/%d/%Y %H:%M:%S')
my_time_diff = timedelta(seconds=216)
my_new_date = my_date + my_time_diff
print(my_new_date.strftime('%m/%d/%Y %H:%M:%S'))

有用的资源：

• https://docs.python.org/2/library/datetime.html