Convert column of date objects in Pandas DataFrame to strings

Question

How to convert a column consisting of datetime64 objects to a strings that would read
01-11-2013 for today’s date of November 1.

I have tried

df['DateStr'] = df['DateObj'].strftime('%d%m%Y')

but I get this error

AttributeError: ‘Series’ object has no attribute ‘strftime’

Asked By: user2333196

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Source

Answer 1

In [6]: df = DataFrame(dict(A = date_range('20130101',periods=10)))

In [7]: df
Out[7]: 
                    A
0 2013-01-01 00:00:00
1 2013-01-02 00:00:00
2 2013-01-03 00:00:00
3 2013-01-04 00:00:00
4 2013-01-05 00:00:00
5 2013-01-06 00:00:00
6 2013-01-07 00:00:00
7 2013-01-08 00:00:00
8 2013-01-09 00:00:00
9 2013-01-10 00:00:00

In [8]: df['A'].apply(lambda x: x.strftime('%d%m%Y'))
Out[8]: 
0    01012013
1    02012013
2    03012013
3    04012013
4    05012013
5    06012013
6    07012013
7    08012013
8    09012013
9    10012013
Name: A, dtype: object

Answered By: Jeff

Answer 2

As of version 17.0, you can format with the dt accessor:

df['DateStr'] = df['DateObj'].dt.strftime('%d%m%Y')

Answered By: Kamil Sindi

Answer 3

It works directly if you first set as index. Then essentially you pass a ‘DatetimeIndex’ object and not a ‘Series’

df = df.set_index('DateObj').copy()    
df['DateStr'] = df.index.strftime('%d%m%Y')

Answered By: vasiliskatr

Convert column of date objects in Pandas DataFrame to strings

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