Python/Pandas 仅将字符串转换为时间

Question

我在 Python 2.7 中有以下 Pandas 数据框。

import pandas as pd
trial_num = [1,2,3,4,5]
sail_rem_time = ['11:33:11','16:29:05','09:37:56','21:43:31','17:42:06']
dfc = pd.DataFrame(zip(*[trial_num,sail_rem_time]),columns=['Temp_Reading','Time_of_Sail'])
print dfc

数据框如下所示:

  Temp_Reading Time_of_Sail
             1     11:33:11
             2     16:29:05
             3     09:37:56
             4     21:43:31
             5     17:42:06

此数据框来自 *.csv 文件。我使用 Pandas 将 *.csv 文件作为 Pandas 数据框读取。当我使用 print dfc.dtypes 时，它显示列 Time_of_Sail 具有数据类型 object。我想将此列转换为 datetime 数据类型，但我只想要时间部分 - 我不想要年、月、日。

我可以试试这个:

dfc['Time_of_Sail'] = pd.to_datetime(dfc['Time_of_Sail'])
dfc['Time_of_Sail'] = [time.time() for time in dfc['Time_of_Sail']]

但问题是当我运行 print dfc.dtypes 时，它仍然显示列 Time_of_Sail 是 object。

有没有办法将此列转换为只有时间的日期时间格式？

其他信息:

要创建上述数据框和输出，这也可以:

import pandas as pd
trial_num = [1,2,3,4,5]
sail_rem_time = ['11:33:11','16:29:05','09:37:56','21:43:31','17:42:06']
data = [
    [trial_num[0],sail_rem_time[0]],
    [trial_num[1],sail_rem_time[1]],[trial_num[2],sail_rem_time[2]],
    [trial_num[3],sail_rem_time[3]]
    ]
dfc = pd.DataFrame(data,columns=['Temp_Reading','Time_of_Sail'])
dfc['Time_of_Sail'] = pd.to_datetime(dfc['Time_of_Sail'])
dfc['Time_of_Sail'] = [time.time() for time in dfc['Time_of_Sail']]
print dfc
print dfc.dtypes

Answer 1

这两行:

dfc['Time_of_Sail'] = pd.to_datetime(dfc['Time_of_Sail'])
dfc['Time_of_Sail'] = [time.time() for time in dfc['Time_of_Sail']]

可以写成:

dfc['Time_of_Sail'] = pd.to_datetime(dfc['Time_of_Sail'],format= '%H:%M:%S' ).dt.time