datetime to string with series in python pandas

There is no str accessor for datetimes and you can't do dates.astype(str) either, you can call apply and use datetime.strftime:

In [73]:

dates = pd.to_datetime(pd.Series(['20010101', '20010331']), format = '%Y%m%d')
dates.apply(lambda x: x.strftime('%Y-%m-%d'))
Out[73]:
0    2001-01-01
1    2001-03-31
dtype: object

You can change the format of your date strings using whatever you like: strftime() and strptime() Behavior.

Update

As of version 0.17.0 you can do this using dt.strftime

dates.dt.strftime('%Y-%m-%d')

will now work

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

dates.dt.strftime('%Y-%m-%d')

Reference

There is a pandas function that can be applied to DateTime index in pandas data frame.

date = dataframe.index #date is the datetime index
date = dates.strftime('%Y-%m-%d') #this will return you a numpy array, element is string.
dstr = date.tolist() #this will make you numpy array into a list

the element inside the list:

u'1910-11-02'

You might need to replace the 'u'.

There might be some additional arguments that I should put into the previous functions.