如何将以下字符串转换为datetime对象?
"Jun 1 2005 1:33PM"
如何将以下字符串转换为datetime对象?
"Jun 1 2005 1:33PM"
当前回答
以下是使用Pandas将格式化为字符串的日期转换为datetime.date对象的两种解决方案。
import pandas as pd
dates = ['2015-12-25', '2015-12-26']
# 1) Use a list comprehension.
>>> [d.date() for d in pd.to_datetime(dates)]
[datetime.date(2015, 12, 25), datetime.date(2015, 12, 26)]
# 2) Convert the dates to a DatetimeIndex and extract the python dates.
>>> pd.DatetimeIndex(dates).date.tolist()
[datetime.date(2015, 12, 25), datetime.date(2015, 12, 26)]
计时
dates = pd.DatetimeIndex(start='2000-1-1', end='2010-1-1', freq='d').date.tolist()
>>> %timeit [d.date() for d in pd.to_datetime(dates)]
# 100 loops, best of 3: 3.11 ms per loop
>>> %timeit pd.DatetimeIndex(dates).date.tolist()
# 100 loops, best of 3: 6.85 ms per loop
下面是如何转换OP的原始日期时间示例:
datetimes = ['Jun 1 2005 1:33PM', 'Aug 28 1999 12:00AM']
>>> pd.to_datetime(datetimes).to_pydatetime().tolist()
[datetime.datetime(2005, 6, 1, 13, 33),
datetime.datetime(1999, 8, 28, 0, 0)]
使用to_datetime将字符串转换为Pandas时间戳有很多选项,因此如果需要任何特殊信息,请查看文档。
同样,除了.date之外,时间戳还有许多可以访问的财产和方法
其他回答
In [34]: import datetime
In [35]: _now = datetime.datetime.now()
In [36]: _now
Out[36]: datetime.datetime(2016, 1, 19, 9, 47, 0, 432000)
In [37]: print _now
2016-01-19 09:47:00.432000
In [38]: _parsed = datetime.datetime.strptime(str(_now),"%Y-%m-%d %H:%M:%S.%f")
In [39]: _parsed
Out[39]: datetime.datetime(2016, 1, 19, 9, 47, 0, 432000)
In [40]: assert _now == _parsed
查看时间模块中的strptime。它是strftime的逆。
$ python
>>> import time
>>> my_time = time.strptime('Jun 1 2005 1:33PM', '%b %d %Y %I:%M%p')
time.struct_time(tm_year=2005, tm_mon=6, tm_mday=1,
tm_hour=13, tm_min=33, tm_sec=0,
tm_wday=2, tm_yday=152, tm_isdst=-1)
timestamp = time.mktime(my_time)
# convert time object to datetime
from datetime import datetime
my_datetime = datetime.fromtimestamp(timestamp)
# convert time object to date
from datetime import date
my_date = date.fromtimestamp(timestamp)
如果您不想明确指定字符串相对于日期时间格式的格式,可以使用此黑客绕过该步骤:
from dateutil.parser import parse
# Function that'll guess the format and convert it into the python datetime format
def update_event(start_datetime=None, end_datetime=None, description=None):
if start_datetime is not None:
new_start_time = parse(start_datetime)
return new_start_time
# Sample input dates in different formats
d = ['06/07/2021 06:40:23.277000', '06/07/2021 06:40', '06/07/2021']
new = [update_event(i) for i in d]
for date in new:
print(date)
# Sample output dates in Python datetime object
# 2014-04-23 00:00:00
# 2013-04-24 00:00:00
# 2014-04-25 00:00:00
如果要将其转换为其他日期时间格式,只需使用您喜欢的格式修改最后一行,例如date.strftime(“%Y/%m/%d%H:%m:%S.%f”):
from dateutil.parser import parse
def update_event(start_datetime=None, end_datetime=None, description=None):
if start_datetime is not None:
new_start_time = parse(start_datetime)
return new_start_time
# Sample input dates in different formats
d = ['06/07/2021 06:40:23.277000', '06/07/2021 06:40', '06/07/2021']
# Passing the dates one by one through the function
new = [update_event(i) for i in d]
for date in new:
print(date.strftime('%Y/%m/%d %H:%M:%S.%f'))
# Sample output dates in required Python datetime object
# 2021/06/07 06:40:23.277000
# 2021/06/07 06:40:00.000000
# 2021/06/07 00:00:00.000000
尝试运行上面的代码段以获得更好的清晰度。
与Javed的回答类似,我只是想要字符串中的日期-所以结合Simon和Javed逻辑,我们得到:
from dateutil import parser
import datetime
s = '2021-03-04'
parser.parse(s).date()
输出
日期时间日期(2021 3月4日)
arrow为日期和时间提供了许多有用的函数。这段代码为这个问题提供了答案,并表明箭头还能够轻松格式化日期并显示其他地区的信息。
>>> import arrow
>>> dateStrings = [ 'Jun 1 2005 1:33PM', 'Aug 28 1999 12:00AM' ]
>>> for dateString in dateStrings:
... dateString
... arrow.get(dateString.replace(' ',' '), 'MMM D YYYY H:mmA').datetime
... arrow.get(dateString.replace(' ',' '), 'MMM D YYYY H:mmA').format('ddd, Do MMM YYYY HH:mm')
... arrow.get(dateString.replace(' ',' '), 'MMM D YYYY H:mmA').humanize(locale='de')
...
'Jun 1 2005 1:33PM'
datetime.datetime(2005, 6, 1, 13, 33, tzinfo=tzutc())
'Wed, 1st Jun 2005 13:33'
'vor 11 Jahren'
'Aug 28 1999 12:00AM'
datetime.datetime(1999, 8, 28, 0, 0, tzinfo=tzutc())
'Sat, 28th Aug 1999 00:00'
'vor 17 Jahren'
看见http://arrow.readthedocs.io/en/latest/了解更多信息。