matplotlib

With matplotlib, you can create a bunch of different plots in Python. The most basic plot is the line plot. A general recipe is given here.

import matplotlib.pyplot as plt
plt.plot(x,y)
plt.show()

ticks/labels

# Scatter plot
plt.scatter(gdp_cap, life_exp)

# Previous customizations
plt.xscale('log') 
plt.xlabel('GDP per Capita [in USD]')
plt.ylabel('Life Expectancy [in years]')
plt.title('World Development in 2007')

# Definition of tick_val and tick_lab
tick_val = [1000,10000,100000]
tick_lab = ['1k','10k','100k']

# Adapt the ticks on the x-axis
plt.xticks(tick_val,tick_lab)

# After customizing, display the plot
plt.show()

sizes

# Import numpy as np
import numpy as np

# Store pop as a numpy array: np_pop
np_pop=np.array(pop)

# Double np_pop
np_pop=np_pop*2

# Update: set s argument to np_pop
plt.scatter(gdp_cap, life_exp, s = np_pop)

# 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'])

# Display the plot
plt.show()