Intermediate Python

# Line plot (1)


import matplotlib.pyplot as plt
plt.plot(x,y)
plt.show()
# Print the last item from year and pop
print(year[-1])
print(pop[-1])

# Import matplotlib.pyplot as plt
import matplotlib.pyplot as plt

# Make a line plot: year on the x-axis, pop on the y-axis
plt.plot(year,pop)

# Display the plot with plt.show()
plt.show()

Scatter Plot (1)
When you have a time scale along the horizontal axis, the line plot is your friend. But in many other cases, when you're trying to assess if there's a correlation between two variables, for example, the scatter plot is the better choice. Below is an example of how to build a scatter plot.

import matplotlib.pyplot as plt
plt.scatter(x,y)
plt.show()
# Change the line plot below to a scatter plot
plt.scatter(gdp_cap, life_exp)

# Put the x-axis on a logarithmic scale. A correlation will become clear when you display the GDP per capita on a logarithmic scale. Add the line plt.xscale('log')
plt.xscale('log')

# Show plot
plt.show()