How can I undo a time series conversion of a pandas dataframe?

Question

I set the index of my dataframe to a time series:

new_data.index = pd.DatetimeIndex(new_data.index)}

How can I convert this timeseries data back into the original string format?

Answer 1

Pandas index objects often have methods equivalent to those available to series. Here you can use pd.Index.astype :

df = pd.DataFrame(index=['2018-01-01', '2018-05-15', '2018-12-25'])

df.index = pd.DatetimeIndex(df.index)
# DatetimeIndex(['2018-01-01', '2018-05-15', '2018-12-25'],
#               dtype='datetime64[ns]', freq=None)

df.index = df.index.astype(str)
# Index(['2018-01-01', '2018-05-15', '2018-12-25'], dtype='object')

Note strings in Pandas are stored in object dtype series. If you need a specific format, this can also be accommodated:

df.index = df.index.strftime('%d-%b-%Y')
# Index(['01-Jan-2018', '15-May-2018', '25-Dec-2018'], dtype='object')

See Python's strftime directives for conventions.