将Pandas索引从整数更改为日期时间格式

Question

I have a huge size DataFrame that contains index in integer form for date time representation, for example, 20171001 . What I'm going to do is to change the form, for example, 20171001 , to the datetime format, '2017-10-01' .

For simplicity, I generate such a dataframe.

>>> df = pd.DataFrame(np.random.randn(3,2), columns=list('ab'), index=
[20171001,20171002,20171003])
>>> df
             a         b
20171001  2.205108  0.926963
20171002  1.104884 -0.445450
20171003  0.621504 -0.584352
>>> df.index
Int64Index([20171001, 20171002, 20171003], dtype='int64')

If we apply 'to_datetime' to df.index, we have the weird result:

>>> pd.to_datetime(df.index)
DatetimeIndex(['1970-01-01 00:00:00.020171001',
           '1970-01-01 00:00:00.020171002',
           '1970-01-01 00:00:00.020171003'],
          dtype='datetime64[ns]', freq=None)

What I want is DatetimeIndex(['2017-10-01', '2017-10-02', '2017-10--3'], ...) How can I manage this problem? Note that the file is given.

Answer 1

Use format %Y%m%d in pd.to_datetime ie

pd.to_datetime(df.index, format='%Y%m%d')
DatetimeIndex(['2017-10-01', '2017-10-02', '2017-10-03'], dtype='datetime64[ns]', freq=None)

To assign df.index = pd.to_datetime(df.index, format='%Y%m%d')

Answer 2

pd.to_datetime is the panda way of doing it. But here are two alternatives:

import datetime
df.index = (datetime.datetime.strptime(str(i),"%Y%m%d") for i in df.index)

or

import datetime
df.index = df.index.map(lambda x: datetime.datetime.strptime(str(x),"%Y%m%d"))