从SQL数据库导入表并按日期过滤行时，将Pandas列解析为Datetime

Question

我有一个DataFrame名为的with列date。我们如何将“日期”列转换/解析为DateTime对象？

我使用加载了Postgresql数据库中的date列sql.read_frame()。该date列的一个示例是2013-04-04。

我想做的是选择一个数据帧中在一定时期内具有日期列的所有行，例如after2013-04-01和before 2013-04-04。

我在下面的尝试给出了错误 'Series' object has no attribute 'read'

尝试

import dateutil

df['date'] = dateutil.parser.parse(df['date'])

错误

AttributeError                            Traceback (most recent call last)
<ipython-input-636-9b19aa5f989c> in <module>()
     15 
     16 # Parse 'Date' Column to Datetime
---> 17 df['date'] = dateutil.parser.parse(df['date'])
     18 
     19 # SELECT RECENT SALES

C:\Python27\lib\site-packages\dateutil\parser.pyc in parse(timestr, parserinfo, **kwargs)
    695         return parser(parserinfo).parse(timestr, **kwargs)
    696     else:
--> 697         return DEFAULTPARSER.parse(timestr, **kwargs)
    698 
    699

C:\Python27\lib\site-packages\dateutil\parser.pyc in parse(self, timestr, default, ignoretz, tzinfos, **kwargs)
    299             default = datetime.datetime.now().replace(hour=0, minute=0,
    300                                                       second=0, microsecond=0)
--> 301         res = self._parse(timestr, **kwargs)
    302         if res is None:
    303             raise ValueError, "unknown string format"

C:\Python27\lib\site-packages\dateutil\parser.pyc in _parse(self, timestr, dayfirst, yearfirst, fuzzy)
    347             yearfirst = info.yearfirst
    348         res = self._result()
--> 349         l = _timelex.split(timestr)
    350         try:
    351

C:\Python27\lib\site-packages\dateutil\parser.pyc in split(cls, s)
    141 
    142     def split(cls, s):
--> 143         return list(cls(s))
    144     split = classmethod(split)
    145

C:\Python27\lib\site-packages\dateutil\parser.pyc in next(self)
    135 
    136     def next(self):
--> 137         token = self.get_token()
    138         if token is None:
    139             raise StopIteration

C:\Python27\lib\site-packages\dateutil\parser.pyc in get_token(self)
     66                 nextchar = self.charstack.pop(0)
     67             else:
---> 68                 nextchar = self.instream.read(1)
     69                 while nextchar == '\x00':
     70                     nextchar = self.instream.read(1)

AttributeError: 'Series' object has no attribute 'read'

df['date'].apply(dateutil.parser.parse) 给我错误 AttributeError: 'datetime.date' object has no attribute 'read'

df['date'].truncate(after='2013/04/01') 给出错误 TypeError: can't compare datetime.datetime to long

df['date'].dtype返回dtype('O')。它已经是datetime物体了吗？

Answer 1

熊猫已经将其视为datetime对象！因此，您想要的是在两个日期之间选择行，然后可以通过屏蔽来做到这一点：

df_masked = df[(df.date > '2012-04-01') & (df.date < '2012-04-04')]

由于您说由于某种原因从字符串中获取错误，请尝试以下操作：

df_masked = df[(df.date > datetime.date(2012,4,1)) & (df.date < datetime.date(2012,4,4))]