colors.py

'''
Colors
100xp
The code you've written up to now is available in the script on the right.

The next step is making the plot more colorful! To do this, a list col has been
created for you. It's a list with a color for each corresponding country, depending
on the continent the country is part of.

How did we make the list col you ask? The Gapminder data contains a list continent
with the continent each country belongs to. A dictionary is constructed that maps
continents onto colors:

dict = {
    'Asia':'red',
    'Europe':'green',
    'Africa':'blue',
    'Americas':'yellow',
    'Oceania':'black'
}
Nothing to worry about now; you will learn about dictionaries in the next chapter.

Instructions
-Add c = col to the arguments of the plt.scatter() function.
-Change the opacity of the bubbles by setting the alpha argument to 0.8 inside plt.scatter().
Alpha can be set from zero to one, where zero is totally transparent,
and one is not at all transparent.
'''
# Specify c and alpha inside plt.scatter()
plt.scatter(x = gdp_cap, y = life_exp, s = np.array(pop) * 2, c = col, alpha = 0.8)

# Previous customizations
plt.xscale('log') 
plt.xlabel('GDP per Capita [in USD]')
plt.ylabel('Life Expectancy [in years]')
plt.title('World Development in 2007')
plt.xticks([1000,10000,100000], ['1k','10k','100k'])

# Show the plot
plt.show()