python数据框转换多种日期时间格式 [英] python dataframe converting multiple datetime formats
本文介绍了python数据框转换多种日期时间格式的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个像这样的pandas.dataframe("col"列有两种格式):
I have a pandas.dataframe like this ('col' column has two formats):
col val
'12/1/2013' value1
'1/22/2014 12:00:01 AM' value2
'12/10/2013' value3
'12/31/2013' value4
我想将它们转换为日期时间,并且正在考虑使用:
I want to convert them into datetime, and I am considering using:
test_df['col']= test_df['col'].map(lambda x: datetime.strptime(x, '%m/%d/%Y'))
test_df['col']= test_df['col'].map(lambda x: datetime.strptime(x, '%m/%d/%Y %H:%M %p'))
显然,它们中的任何一个都可以为整个df工作.我正在考虑使用try and,但没有任何运气,没有任何建议吗?
Obviously either of them works for the whole df. I'm thinking about using try and except but didn't get any luck, any suggestions?
推荐答案
Just use to_datetime
, it's man/woman enough to handle both those formats:
In [4]:
df['col'] = pd.to_datetime(df['col'])
df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 4 entries, 0 to 3
Data columns (total 2 columns):
col 4 non-null datetime64[ns]
val 4 non-null object
dtypes: datetime64[ns](1), object(1)
memory usage: 96.0+ bytes
df现在看起来像这样:
The df now looks likes this:
In [5]:
df
Out[5]:
col val
0 2013-12-01 00:00:00 value1
1 2014-01-22 00:00:01 value2
2 2013-12-10 00:00:00 value3
3 2013-12-31 00:00:00 value4
这篇关于python数据框转换多种日期时间格式的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!
查看全文