I'm starting a very beginner tutorial for DS/ML. One of the first things to do is to poke at the data they gave me. After doing the typical head() and describe() in pandas, I want to look more carefully at the features that are numerical, to see if there's any correlation between them and the labels (for example, a simple linear relationship).
I've used matplotlib and stuff before, but I want to do this the "correct" way. The tutorial I'm looking at suggests using seaborn, but to be honest it seems difficult to apply to what I'm suggesting (they're looking at more complicated relationships/etc).
I could use matplotlib, but I've never found a smooth, seamless way of making a grid of several plots simultaneously. Doing the "subplot" thing was really clunky. Is there a better way?
What I'd like to do is, let's say I have 4 numerical features, and I want to plot each of them (or their average, etc) vs the label, and display it, so I can quickly see patterns. What's the best way to do this?