return the name of the row(first column) of the maximum difference between two columns

I have a dataframe like this :

  Country   1990  1995 2000 2005 2010  2015
0   Bahrain     5     4    3    2   1    20
1   Maldives   10     9    8    7   6    30
2   Germany    7      4    3    2   1    40
.      ....     ..    ..   ..    ..  ..  ..
.      ....     ..    ..   ..    ..  ..  ..
.      ....     ..    ..   ..    ..  ..  ..

I want to calculate the difference between column 2015 and 1990 and then return the name of the row with the maximum difference.
In this case is Germany.

I wrote this:

highest_growth =(df['2020']-df['1990']).abs().idxmax()

which returns the index of the country with the maximum difference but I want to have the name of the country as a string output.
I don’t want an extra column.Just returning the name of the country with the max value of df[‘2020’]-df[‘1990’].

>Solution :

With the index of the row, you can get the country name by indexing df['Country']:

highest_growth_index = (df['2020']-df['1990']).abs().idxmax()
highest_growth = df['Country'][highest_growth_index]

In one line:

highest_growth = df['Country'][(df['2020']-df['1990']).abs().idxmax()]