Using scatter plots to view bivariate relationships
My sense is that there are few plots that data analysts rely more on than scatter plots, with the possible exception of histograms. We are all very used to looking at relationships that can be illustrated in two dimensions. Scatter plots capture important real-world phenomena (the relationship between variables) and are quite intuitive for most people. This makes them a valuable addition to our visualization toolkit.
You will need Matplotlib and Seaborn for this recipe. We will be working with the
landtemps dataset, which provides the average temperature in 2019 for 12,095 weather stations across the world.
How to do it...
We level up our scatter plot skills from the previous chapter and visualize more complicated relationships. We display the relationship between average temperature, latitude, and elevation by showing multiple scatter plots on one chart, creating 3D scatter plots, and showing multiple regression...