country_worth = data[data.country.isin(selected_countries)][['country','worth']]
country_worth = country_worth.groupby('country').median()

# we visualize the average(median) worth in each country and compare which on has the highest
# or the least
with plt.style.context('fivethirtyeight'):
    country_worth.plot(kind='barh',figsize=(10,6),color='purple',alpha=.8)
    plt.title('Average worth of Forbes 2018 world\nbillioniares across countries.',
              fontsize=15)
    plt.xlabel('worth (millions of US dollars)',fontsize=13)
    plt.ylabel('country',fontsize=13)
    plt.legend(labels=[])
    plt.grid(axis='x')