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
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