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Pandas dataframe.set_index() deletes previous index and column

I just came across a strange phenomenon with Pandas DataFrames, when setting index using DataFrame.set_index('some_index') the old column that was also an index is deleted! Here is an example:

import pandas as pd
df = pd.DataFrame({'month': [1, 4, 7, 10],'year': [2012, 2014, 2013, 2014],'sale':[55, 40, 84, 31]})
df_mn=df.set_index('month')
>>> df_mn
       sale  year
month            
1        55  2012
4        40  2014
7        84  2013
10       31  2014

Now I change the index to year:

df_mn.set_index('year')
      sale
year      
2012    55
2014    40
2013    84
2014    31

.. and the month column was removed with the index. This is vary irritating because I just wanted to swap the DataFrame index.

Is there a way to not have the previous column that was an index from being deleted? Maybe through something like: DataFrame.set_index('new_index',delete_previous_index=False)

Thanks for any advice

Solution

  • Both of the current top answers solve part of the problem.

    The complete solution is:

    df_mn.reset_index().set_index('year', drop=False)

    Calling .reset_index() first will convert the initial index into a column, so you will not lose it when calling set_index().

    Adding drop=False to the set_index call means that year is not dropped when set as the index.