Pandas: changing dataframe date index format

Question

Would like to change the Date index of the dataframe from the default style into '%m/%d/%Y' format.

In: df
Out: 

  Date     Close     

2006-01-24  48.812471
2006-01-25  47.448712
2006-01-26  53.341202
2006-01-27  58.728122
2006-01-30  59.481986
2006-01-31  55.691974

df.index

 Out: 
 DatetimeIndex(['2006-01-04', '2006-01-05', '2006-01-06', '2006-01-09',
           '2006-01-10', '2006-01-11', '2006-01-12', '2006-01-13',
           '2006-01-17', '2006-01-18',
           ...
           '2018-02-21', '2018-02-22', '2018-02-23', '2018-02-26',
           '2018-02-27', '2018-02-28', '2018-03-01', '2018-03-02',
           '2018-03-05', '2018-03-06'],
          dtype='datetime64[ns]', name=u'Date', length=3063, freq=None)

Into:

In: df1
Out: 

 Date     Close     

01/24/2006  48.812471
01/25/2006  47.448712
01/26/2006  53.341202
01/27/2006  58.728122
01/28/2006  59.481986
01/29/2006  55.691974

I tried this method before...

 df1.index = pd.to_datetime(df.index, format = '%m/%d/%Y')
 df1.index = df.dt.strftime('%Y-%m-%d')

 AttributeError: 'DataFrame' object has no attribute 'dt'

Answer 1

Use DatetimeIndex.strftime - instead dt need index:

df1.index = pd.to_datetime(df1.index, format = '%m/%d/%Y').strftime('%Y-%m-%d')

What is same:

df1.index = pd.to_datetime(df1.index, format = '%m/%d/%Y')
df1.index = df1.index.strftime('%Y-%m-%d')

EDIT if need convert DatetimeIndex to another string format:

print (df1.index)
DatetimeIndex(['2006-01-24', '2006-01-25', '2006-01-26', '2006-01-27',
               '2006-01-30', '2006-01-31'],
              dtype='datetime64[ns]', name='Date', freq=None)


df1.index = df1.index.strftime('%m/%d/%Y')
print (df1)
                Close
01/24/2006  48.812471
01/25/2006  47.448712
01/26/2006  53.341202
01/27/2006  58.728122
01/30/2006  59.481986
01/31/2006  55.691974