import matplotlib.pyplot as plt
year =[list]
pop = [list]

plt.plot(year,pop)
#plt.scatter(gdp_cap,life_exp)
#plt.xscale('log') 
#以log的形式表现

#information show on the plot 
plt.xlabel('year')
plt.ylabel('polulation')
plt.title('wolrd')
plt.yticks([0,2,4,6,8,10],['0','2B','4B','6B','8B','10B'])
#the ticks corresponding to the numbers 0, 2 and 4 will be replaced by '0', '2B' and '4B', respectively.
plt.show()

# Scatter plot
#Wouldn't it be nice if the size of the dots corresponds to the population,
#pop list contains population numbers for each country expressed in millions.
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'])

# Additional customizations
plt.text(1550, 71, 'India')
plt.text(5700, 80, 'China')

# Add grid() call

plt.grid(True)
# Show the plot
plt.show()

add plt.grid(True) after the plt.text() calls so that gridlines are drawn on the plot

Addc = colto the arguments of theplt.scatter()function.

• Change the opacity of the bubbles by setting thealphaargument to0.8insideplt.scatter()Alpha can be set from zero to one, where zero is totally transparent, and one is not at all transparent.