pandas 将字符串日期时间转换为熊猫日期时间
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Convert string date time to pandas datetime
提问by Sourabh Saxena
I am new to Pandas and Python. I want to do some date time operations in my script. I am getting date time information from a csv file in following format: 01APR2017 6:59
我是 Pandas 和 Python 的新手。我想在我的脚本中做一些日期时间操作。我从以下格式的 csv 文件中获取日期时间信息： 01APR2017 6:59
How to convert it into pandas datetime format? Something like: 2017-04-01 06:59:00
如何将其转换为Pandas日期时间格式？类似于： 2017-04-01 06:59:00
回答by jezrael
You can use to_datetimewith parameter format:
您可以使用to_datetime参数format：
s = pd.Series(['01APR2017 6:59','01APR2017 6:59'])
print (s)
0 01APR2017 6:59
1 01APR2017 6:59
dtype: object
print (pd.to_datetime(s, format='%d%b%Y %H:%M'))
0 2017-04-01 06:59:00
1 2017-04-01 06:59:00
dtype: datetime64[ns]
Another possible solution is use date_parserin read_csv:
另一种可能的解决方案是使用date_parser在read_csv：
import pandas as pd
from pandas.compat import StringIO
temp=u"""date
01APR2017 6:59
01APR2017 6:59"""
#after testing replace 'StringIO(temp)' to 'filename.csv'
parser = lambda x: pd.datetime.strptime(x, '%d%b%Y %H:%M')
df = pd.read_csv(StringIO(temp), parse_dates=[0], date_parser=parser)
print (df)
date
0 2017-04-01 06:59:00
1 2017-04-01 06:59:00
print (df.date.dtype)
datetime64[ns]
EDIT by comment:
通过评论编辑：
If values cannot be parsed to datetime, add parameter errors='coerce'for convert to NaT:
如果无法将值解析为datetime，请添加errors='coerce'用于转换为的参数NaT：
s = pd.Series(['01APR2017 6:59','01APR2017 6:59', 'a'])
print (s)
0 01APR2017 6:59
1 01APR2017 6:59
2 a
dtype: object
print (pd.to_datetime(s, format='%d%b%Y %H:%M', errors='coerce'))
0 2017-04-01 06:59:00
1 2017-04-01 06:59:00
2 NaT
dtype: datetime64[ns]
