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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()

Let's continue with the gdp_cap versus life_exp plot, the GDP and life expectancy data for different countries in 2007. Maybe a scatter plot will be a better alternative?

Again, the matplotlib.pyplot package is available as plt.

This exercise is part of the course

Intermediate Python

View Course

Exercise instructions

  • Change the line plot that's coded in the script to a scatter plot.
  • A correlation will become clear when you display the GDP per capita on a logarithmic scale. Add the line plt.xscale('log').
  • Finish off your script with plt.show() to display the plot.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Change the line plot below to a scatter plot
plt.plot(gdp_cap, life_exp)

# Put the x-axis on a logarithmic scale


# Show plot
Edit and Run Code