There is a df Pandas dataframe: date av_temp deviations country year decade 577457 2013-05-01 19.059 1.022 Zimbabwe 2013 2010-2020 577458 2013-06-01 17.613 0.473 Zimbabwe 2013 2010-2020 577459 2013-07-01 17.000 0.453 Zimbabwe 2013 2010-2020 577460 2013-08-01 19.759 0.717 Zimbabwe 2013 2010-2020 Write a function that: 1) leave only the rows in the year column with a value higher than 1980 2) calculates the average temperature of the countries (the average of the av_temp column) 3) builds a list of the 20 coldest countries in ascending av_temp order

def calc_av_temp(df):
    df = df[df['year']>1980]
    df = df.groupby('country').agg({'av_temp': np.mean})
    return df.sort_values('av_temp').head(20)