[英]'NaTType' object has no attribute 'days'
I have a column in my dataset which represents a date in ms and sometimes its values is nan
(actually my columns is of type str
and sometimes its valus is 'nan'
). 我的数据集中有一个列,表示以ms为单位的日期,有时其值为nan
(实际上我的列是str
类型,有时它的值是'nan'
)。 I want to compute the epoch in days of this column. 我想在本专栏的几天内计算时代。 The problem is that when doing the difference of two dates: 问题在于,当做两个日期的差异时:
(pd.to_datetime('now') - pd.to_datetime(np.nan)).days
if one is nan
it is converted to NaT
and the difference is of type NaTType
which hasn't the attribute days
. 如果一个是nan
,则转换为NaT
,差异是NaTType
类型,它没有属性days
。
In my case I would like to have nan
as a result. 在我的情况下,我希望有nan
作为结果。
Other approach I have tried: np.datetime64
cannot be used, since it cannot take as argument nan
. 我尝试过的其他方法: np.datetime64
不能使用,因为它不能作为参数nan
。 My data cannot be converted to int
since int
doesn't have nan
. 我的数据无法转换为int
因为int
没有nan
。
It will just work even if you filter first: 即使您先过滤它也会起作用:
In [201]:
df = pd.DataFrame({'date':[dt.datetime.now(), pd.NaT, dt.datetime(2015,1,1)]})
df
Out[201]:
date
0 2015-08-28 12:12:12.851729
1 NaT
2 2015-01-01 00:00:00.000000
In [203]:
df.loc[df['date'].notnull(), 'days'] = (pd.to_datetime('now') - df['date']).dt.days
df
Out[203]:
date days
0 2015-08-28 12:12:12.851729 -1
1 NaT NaN
2 2015-01-01 00:00:00.000000 239
对我来说,从pandas 0.19.2升级到pandas 0.20.3有助于解决此错误。
pip install --upgrade pandas
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