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?
DataFrame
date
DateTime
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。
sql.read_frame()
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。
2013-04-01
我在下面的尝试给出了错误 'Series' object has no attribute 'read'
'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'].apply(dateutil.parser.parse)
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'].truncate(after='2013/04/01')
TypeError: can't compare datetime.datetime to long
df['date'].dtype返回dtype('O')。它已经是datetime物体了吗?
df['date'].dtype
dtype('O')
datetime
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))]