def average_gdp():

    Top15['avgGDP'] = Top15[[str(year) for year in range(2006, 2016)]].apply(lambda x: x.mean(), axis=1)
    avgGDP = Top15['avgGDP'].sort_values(ascending=False)
    sixth_largest = avgGDP.iloc[5]
    
    return (sixth_largest)

From Snap code above

I do like traditional one like this but. Seem not what is the purpose to create in NumPy and Pandas, How to improve this code.
I would like to create with numpy function.

Create column name avgGDP sort value on avgGDP as descending. And get the sixth largest GDP from avgGDP.