我一直在阅读很多将字符串转换为日期时间的问题,但我没有找到类似于此数据框中显示的字符串日期。
idAviso timestamp idpostulante
1111413600 2018-02-28T20:40:28.079-0500 0z5VvGv
1112368499 2018-02-28T20:51:02.844-0500 0z5VvGv
1112369554 2018-02-28T20:43:50.396-0500 0z5VvGv
1112358250 2018-02-27T16:02:19.303-0500 0zB026d
1112358250 2018-02-27T16:02:30.036-0500 0zB026d
我的目标是将列timestamp
转换为类似的内容,然后我可以将其用于某些分析
idAviso timestamp idpostulante
1111413600 2018-02-28 0z5VvGv
1112368499 2018-02-28 0z5VvGv
1112369554 2018-02-28 0z5VvGv
1112358250 2018-02-27 0zB026d
1112358250 2018-02-27 0zB026d
timestamp
现在应该是日期时间变量
答案 0 :(得分:1)
只需使用.str[:10]
删除字符串,然后像这样使用pd.to_datetime()
:
df['timestamp'] = pd.to_datetime(df['timestamp'].str[:10])
其他选择:
df['timestamp'] = df['timestamp'].apply(pd.Timestamp)
df['timestamp'] = pd.to_datetime(df['timestamp']) # offset by 5 hours
完整示例:
import pandas as pd
import numpy as np
data = '''\
idAviso timestamp idpostulante
1111413600 2018-02-28T20:40:28.079-0500 0z5VvGv
1112368499 2018-02-28T20:51:02.844-0500 0z5VvGv
1112369554 2018-02-28T20:43:50.396-0500 0z5VvGv
1112358250 2018-02-27T16:02:19.303-0500 0zB026d
1112358250 2018-02-27T16:02:30.036-0500 0zB026d'''
file = pd.compat.StringIO(data)
df = pd.read_csv(file, sep='\s+')
df['timestamp'] = pd.to_datetime(df['timestamp'].str[:10])
print(df)
返回:
idAviso timestamp idpostulante
0 1111413600 2018-02-28 0z5VvGv
1 1112368499 2018-02-28 0z5VvGv
2 1112369554 2018-02-28 0z5VvGv
3 1112358250 2018-02-27 0zB026d
4 1112358250 2018-02-27 0zB026d
另见:
答案 1 :(得分:1)
这是带有偏移的ISO8061时间格式。
In [1]: x= '2018-02-28T20:40:28.079-0500'
In [2]: from dateutil.parser import parse
In [3]: parse(x)
Out[3]: datetime.datetime(2018, 2, 28, 20, 40, 28, 79000, tzinfo=tzoffset(None, -18000))
在pandas Dataframe中使用它
In [7]: df = pd.DataFrame([x])
In [8]: df
Out[8]:
0
0 2018-02-28T20:40:28.079-0500
In [9]: df[0]
Out[9]:
0 2018-02-28T20:40:28.079-0500
Name: 0, dtype: object
In [10]: df[0].apply(parse)
Out[10]:
0 2018-02-28 20:40:28.079000-05:00
Name: 0, dtype: datetime64[ns, tzoffset(None, -18000)]