我有一个日期时间系列,我想只保留系列中的“Hour-Miniute-Second”字符串,并删除Year-Month-Date字符串。 那我该怎么办?
原创系列:
0 2000-12-31 22:12:40
1 2000-12-31 22:35:09
2 2000-12-31 22:32:48
3 2000-12-31 22:04:35
4 2001-01-06 23:38:11
5 2000-12-31 22:37:48
……
目标:
0 22:12:40
1 22:35:09
2 22:32:48
3 22:04:35
4 23:38:11
5 22:37:48
……
很明显,原始系列已经使用pandas.to_datetime()
从unix时间戳系列中翻译过来。但是我无法使用这种方法达到我的目标:(
感谢任何建议!
答案 0 :(得分:2)
使用dt.strftime
:
#if necessary convert to datetime
#df['date'] = pd.to_datetime(df['date'])
print (df.dtypes)
date datetime64[ns]
dtype: object
df['time'] = df['date'].dt.strftime('%H:%M:%S')
print (df)
date time
0 2000-12-31 22:12:40 22:12:40
1 2000-12-31 22:35:09 22:35:09
2 2000-12-31 22:32:48 22:32:48
3 2000-12-31 22:04:35 22:04:35
4 2001-01-06 23:38:11 23:38:11
5 2000-12-31 22:37:48 22:37:48
或转换为string
,split
并按lists
选择str[1]
的第二个值:
#if dtype of date column is object (obviously string), omit astype
df['time'] = df['date'].astype(str).str.split().str[1]
print (df)
date time
0 2000-12-31 22:12:40 22:12:40
1 2000-12-31 22:35:09 22:35:09
2 2000-12-31 22:32:48 22:32:48
3 2000-12-31 22:04:35 22:04:35
4 2001-01-06 23:38:11 23:38:11
5 2000-12-31 22:37:48 22:37:48
答案 1 :(得分:0)
使用:日期时间
from datetime import datetime
your_datetime = "2017-01-01 23:00:00"
dt = datetime.strptime(your_datetime , "%Y-%m-%d %H:%M:%S").strftime('%H:%M:%S')
print dt
答案 2 :(得分:0)
你已经有了一些不错的答案。但是,它们将它们存储为字符串,您可能希望将它们存储为实际的datetime.time
对象:
import pandas as pd
df = pd.DataFrame([
{'date': '2000-12-31 22:12:40'},
{'date': '2000-12-31 22:35:09'},
{'date': '2000-12-31 22:32:48'},
{'date': '2000-12-31 22:04:35'},
{'date': '2001-01-06 23:38:11'},
{'date': '2000-12-31 22:37:48'},
])
df['date'] = pd.to_datetime(df['date'])
df['time'] = df['date'].dt.time
print(df)
print(df['time'].dtype)
print(type(df['time'][0]))
date time
0 2000-12-31 22:12:40 22:12:40
1 2000-12-31 22:35:09 22:35:09
2 2000-12-31 22:32:48 22:32:48
3 2000-12-31 22:04:35 22:04:35
4 2001-01-06 23:38:11 23:38:11
5 2000-12-31 22:37:48 22:37:48
object
<class 'datetime.time'>
修改强>
注意到您的目标没有date
列。将以下内容添加到最后:
del df['date']
print(df)
time
0 22:12:40
1 22:35:09
2 22:32:48
3 22:04:35
4 23:38:11
5 22:37:48