Max value using idxmax

Question

I am trying to calculate the biggest difference between summer gold medal counts and winter gold medal counts relative to their total gold medal count. The problem is that

Answer 1

I an pretty new to python or programming as a whole. So my solution would be the most novice ever! I love to create variables; so you'll see a lot in the solution.

    def answer_three:
      a = df.loc[df['Gold'] > 0,'Gold']
           #Boolean masking that only prints the value of Gold that matches the condition as stated in the question; in this case countries who had at least one Gold medal in the summer seasons olympics.

      b = df.loc[df['Gold.1'] > 0, 'Gold.1']
           #Same comment as above but 'Gold.1' is Gold medals in the winter seasons 

      dif = abs(a-b)

           #returns the abs value of the difference between a and b.

      dif.dropna()

           #drops all 'Nan' values in the column.

      tots = a + b

           #i only realised that this step wasn't essential because the data frame had already summed it up in the column 'Gold.2'

      tots.dropna()

      result = dif.dropna()/tots.dropna()

      returns result.idxmax

           # returns the index value of the max result