Question

import datetime as datetime
datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S')

生成

AttributeError Traceback（最近一次调用   最后）in（）         1导入日期时间为datetime   ----＆GT; 2 datetime.strptime（'2013-01-01 09:10:12'，'％Y-％m-％d％H：％M：％S'）         3 z = minidf ['日期']         4 z

AttributeError：'module'对象没有属性'strptime'

我的目标是转换格式仍为数据对象的pandas dataframe列

import datetime as datetime
#datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S')
z = minidf['Dates']

0     2015-05-13 23:53:00
1     2015-05-13 23:53:00
2     2015-05-13 23:33:00
3     2015-05-13 23:30:00
4     2015-05-13 23:30:00
5     2015-05-13 23:30:00
6     2015-05-13 23:30:00
7     2015-05-13 23:30:00
8     2015-05-13 23:00:00
9     2015-05-13 23:00:00
10    2015-05-13 22:58:00
Name: Dates, dtype: object

奖金问题是，我从一个包含更多列的较大文件中使用pd.read_csv函数获取此列。是否可以传递参数，以便pd.read_csv直接将其转换为dtype: datetime64[ns]格式

Answer 1

我认为您可以用来转换to_datetime：

print pd.to_datetime('2013-01-01 09:10:12', format='%Y-%m-%d %H:%M:%S')
2013-01-01 09:10:12

print pd.to_datetime('2013-01-01 09:10:12')
2013-01-01 09:10:12

如果您需要在功能read_csv中进行转换，请添加参数parse_dates：

df = pd.read_csv('filename',  parse_dates=['Dates'])

样品：

import pandas as pd
import io

temp=u"""Dates
2015-05-13 23:53:00
2015-05-13 23:53:00
2015-05-13 23:33:00
2015-05-13 23:30:00
2015-05-13 23:30:00
2015-05-13 23:30:00
2015-05-13 23:30:00
2015-05-13 23:30:00
2015-05-13 23:00:00
2015-05-13 23:00:00
2015-05-13 22:58:00
"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp),  parse_dates=['Dates'])
print df
                 Dates
0  2015-05-13 23:53:00
1  2015-05-13 23:53:00
2  2015-05-13 23:33:00
3  2015-05-13 23:30:00
4  2015-05-13 23:30:00
5  2015-05-13 23:30:00
6  2015-05-13 23:30:00
7  2015-05-13 23:30:00
8  2015-05-13 23:00:00
9  2015-05-13 23:00:00
10 2015-05-13 22:58:00

print df.dtypes
Dates    datetime64[ns]
dtype: object

to_datetime的另一个解决方案：

print pd.to_datetime(df['Dates'])

样品：

print df
                  Dates
0   2015-05-13 23:53:00
1   2015-05-13 23:53:00
2   2015-05-13 23:33:00
3   2015-05-13 23:30:00
4   2015-05-13 23:30:00
5   2015-05-13 23:30:00
6   2015-05-13 23:30:00
7   2015-05-13 23:30:00
8   2015-05-13 23:00:00
9   2015-05-13 23:00:00
10  2015-05-13 22:58:00

print df.dtypes
Dates    object

df['Dates'] = pd.to_datetime(df['Dates'])
print df
                 Dates
0  2015-05-13 23:53:00
1  2015-05-13 23:53:00
2  2015-05-13 23:33:00
3  2015-05-13 23:30:00
4  2015-05-13 23:30:00
5  2015-05-13 23:30:00
6  2015-05-13 23:30:00
7  2015-05-13 23:30:00
8  2015-05-13 23:00:00
9  2015-05-13 23:00:00
10 2015-05-13 22:58:00

print df.dtypes
Dates    datetime64[ns]
dtype: object

Answer 2

AttributeError：＆＃39; module＆＃39;对象没有属性＆＃39; strptime＆＃39;

strptime不适用于datetime，而是datetime.datetime

>>> from datetime import datetime
>>> datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S')
datetime.datetime(2013, 1, 1, 9, 10, 12)

Answer 3

仅导入模块

>>> import datetime
>>> datetime.datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S')
datetime.datetime(2013, 1, 1, 9, 10, 12)

将类从模块导入当前上下文：

>>> from datetime import datetime
>>> datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S')
datetime.datetime(2013, 1, 1, 9, 10, 12)
>>>

Python熊猫中的日期时间strptime：出了什么问题？

3 个答案: