Now that we understand our features individually, it is time to start exploring whether there are any relationships between them. Bivariate EDA techniques are used to explore pairs of variables, and start understanding how they relate to each other.
How many pair relationships will we have? For a dataset of k features, we will have 
distinct pairs. In our original dataset we have 10 features, so we will have 
pairs of variables to analyze. This is a very small dataset, (in terms of the number of features)—but as you can see, the formula is basically a quadratic term, so for a large dataset, the number of pairs goes up quickly.
Of course, you don't actually have to analyze every possible pair; only choose those that are interesting or which will answer a particular question you may have about the dataset. In addition, pandas and Seaborn will make our task...
