AttributeError：只能使用具有 0yrs 0mon 格式的 datetimelike 值的 .dt 访问器

Question

我正在尝试将日期字符串格式转换为数字，但出现了一些错误， 我的日期栏是这样的：

train['AVERAGE_ACCT_AGE'].head(6)
0     0yrs 0mon
1    1yrs 11mon
2     0yrs 0mon
3     0yrs 8mon
4     0yrs 0mon
5     1yrs 9mon
Name: AVERAGE_ACCT_AGE, dtype: object

我尝试使用此代码将 DateTime 格式添加到该变量。

train['AVERAGE_ACCT_AGE']=pd.to_datetime(train['AVERAGE.ACCT.AGE'], format='%Y%m')
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
~\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py in _convert_listlike(arg, box, format, name, tz)
    376             try:
--> 377                 values, tz = conversion.datetime_to_datetime64(arg)
    378                 return DatetimeIndex._simple_new(values, name=name, tz=tz)

pandas\_libs\tslibs\conversion.pyx in pandas._libs.tslibs.conversion.datetime_to_datetime64()

TypeError: Unrecognized value type: <class 'str'>

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-49-13f5c298f460> in <module>()
----> 1 train['AVERAGE_ACCT_AGE']=pd.to_datetime(train['AVERAGE.ACCT.AGE'], format='%Y-%m')

~\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py in to_datetime(arg, errors, dayfirst, yearfirst, utc, box, format, exact, unit, infer_datetime_format, origin, cache)
    449         else:
    450             from pandas import Series
--> 451             values = _convert_listlike(arg._values, True, format)
    452             result = Series(values, index=arg.index, name=arg.name)
    453     elif isinstance(arg, (ABCDataFrame, MutableMapping)):

~\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py in _convert_listlike(arg, box, format, name, tz)
    378                 return DatetimeIndex._simple_new(values, name=name, tz=tz)
    379             except (ValueError, TypeError):
--> 380                 raise e
    381 
    382     if arg is None:

~\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py in _convert_listlike(arg, box, format, name, tz)
    366                     dayfirst=dayfirst,
    367                     yearfirst=yearfirst,
--> 368                     require_iso8601=require_iso8601
    369                 )
    370 

pandas\_libs\tslib.pyx in pandas._libs.tslib.array_to_datetime()

pandas\_libs\tslib.pyx in pandas._libs.tslib.array_to_datetime()

ValueError: time data 0yrs 0mon doesn't match format specified

之后，我尝试使用此代码将错误忽略添加到列中。

train['AVERAGE_ACCT_AGE']=pd.to_datetime(train['AVERAGE.ACCT.AGE'], format='%Y%m',errors='ignore',infer_datetime_format=True)

它添加了日期时间格式，然后是这段代码

    train['yrs']=train['AVERAGE_ACCT_AGE'].dt.year
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-50-39b8c6e07f77> in <module>()
----> 1 train['yrs']=train['AVERAGE_ACCT_AGE'].dt.year

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __getattr__(self, name)
   4366         if (name in self._internal_names_set or name in self._metadata or
   4367                 name in self._accessors):
-> 4368             return object.__getattribute__(self, name)
   4369         else:
   4370             if self._info_axis._can_hold_identifiers_and_holds_name(name):

~\Anaconda3\lib\site-packages\pandas\core\accessor.py in __get__(self, obj, cls)
    130             # we're accessing the attribute of the class, i.e., Dataset.geo
    131             return self._accessor
--> 132         accessor_obj = self._accessor(obj)
    133         # Replace the property with the accessor object. Inspired by:
    134         # http://www.pydanny.com/cached-property.html

~\Anaconda3\lib\site-packages\pandas\core\indexes\accessors.py in __new__(cls, data)
    323             pass  # we raise an attribute error anyway
    324 
--> 325         raise AttributeError("Can only use .dt accessor with datetimelike "
    326                              "values")

请帮助我如何将对象类型转换为数字类型。我想要分开几年和几个月的专栏。

AttributeError: Can only use .dt accessor with datetimelike values

Answer 1

该列不是Datetime 格式。

这是一种将其转换为数字的快速方法。 我使用的行数超出了需要。

# doing this so we can have it in string format
train['AVERAGE_ACCT_AGE'] = train['AVERAGE_ACCT_AGE'].astype(str)

#Now remove the trailing or any such spaces
train['AVERAGE_ACCT_AGE'] = train['AVERAGE_ACCT_AGE'].map(lambda x: x.strip())

#Next we split and expand the column into 2 columns:
train[['yrs','months']] = train['AVERAGE_ACCT_AGE'].str.split(' ',n=1,expand=True)

#remove characters from new columns, 
#I am assuming the characters remain the same

train['yrs'] = train['yrs'].str.replace('yrs','')
train['months'] = train['months'].str.replace('mon','')
# Convert yrs to float
train['yrs'] = train['yrs'].astype('float')
# Convert months to float
train['months'] = train['yrs'].astype('float')

希望对你有帮助。