How to plot and interpret pairwise plots in python.
What are Pairwise plots?
Pairwise plots allow us to see both the distribution of a single variable and the relationship between two variables. They are a great method to identify follow-up analysis trends and help us select the best set of features to explain a relationship between two variables.
The pairwise plots by default plot only the numerical values, although later on, you can use the hue feature to plot categorical values, as we shall see in the blog.
How to plot Pairwise plots in Python
You will need to import the seaborn library. I am also using a real-life data set for marketing
First load the dataset
To create a pairwise plot, we shall use this code
Interpretation
The first row at the bottom represents sales on the y-axis, then the middle one represents social media, and the one at the top represents radio on the y-axis. The first column on the left represents radio on the x-axis, the middle one social media, and the one on the far right sales.
So the scatter plots help us to determine the relationship between the different variables, and the histograms on the main diagonal axis show us the distribution of the individual variable.
For example, the first scatter plot on the bottom left shows that there is a positive linear relationship between sales and radio
The next scatter plot in the middle shows that there is a linear relationship between social media and sales
The histogram on the bottom right shows the distribution of sales.
Adding the categorical variable TV, we use hue.
Advantages
It can be used to determine which features are useful for our classification.
Limitations
They can only be used when the variables to be plotted are few.
I hope you find this blog helpful😊