Retain the previous index of the dataframe as a column after setting another column as a index

Question

I have a dataframe(test4) of the following kind with Yrs as a index column-

                  Prs_90      Prs_80      Prs_70
        Yrs                                     
        2012  499.934588  521.512345  425.189729
        2013  579.063531  477.782099  256.382494
        2014  458.415624  456.480642  363.309507
        2015  422.547029  320.282754  578.728535

Now , I want to set Prs_90 as a index which I am doing using test4.set_index("Prs_90", inplace = True)

but it is removing the Yrs index completely which I want to retain.

                       Prs_80      Prs_70
           Prs_90                            
       854.819691  514.883611  338.596315
       780.394013  488.100756  417.143175
       752.188841  326.476833  644.588971
       703.369157  542.508996  361.643381

Expected Output-

                   Prs_80      Prs_70   Yrs
       Prs_90                            
   854.819691  514.883611  338.596315   2012
   780.394013  488.100756  417.143175   2013
   752.188841  326.476833  644.588971   2014
   703.369157  542.508996  361.643381   2015

How to do it?

but I don't want the previous index as one of the current index — Bing, Jan 31 '19 at 09:16
Okay, you can use `df.assign(Yrs=df.index).set_index('Prs_90')`. — cs95, Jan 31 '19 at 09:17
Why would you want a `float` index? Seems like an XY problem. — jpp, Jan 31 '19 at 09:39
Almost certainly, you're going about "some other problem" incorrectly - but beyond the scope of this question, clearly. — jpp, Jan 31 '19 at 09:43
I want to implement the solution mentioned in this answer https://stackoverflow.com/questions/54435024/choose-r-outcomes-from-n-possibilities-efficiently-in-pandas — Bing, Jan 31 '19 at 09:44

Peter Sorensen · Answer 1 · 2019-01-31T09:32:24.740

1

Before introducing the new Prs_90 index you can call

df = df.reset_index()

reset_index() will make the present index into a column.

edited Jan 31 '19 at 09:32

answered Jan 31 '19 at 09:22

Peter Sorensen

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score 1 · Accepted Answer · answered Jan 31 '19 at 09:28

1

You could try the following:

test4.reset_index(drop=False).set_index("Prs_90")

answered Jan 31 '19 at 09:28

run-out

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Retain the previous index of the dataframe as a column after setting another column as a index

2 Answers2