As an activity, please mess around with the fake input data where you want. You can download the data and mess around with the spreadsheet. Read it from your local hard drive instead of from HTTP, and see what kind of differences you can have. Maybe you can fabricate a dataset that has a different behavior and has a better model that fits it. Maybe you can make a wiser choice of features to base your model off of. So, feel free to mess around with that and let's move on.

There you have it: multivariate analysis and an example of it running. Just as important as the concept of multivariate analysis, which we explored, was some of the stuff that we did in that Python notebook. So, you might want to go back there and study exactly what's going on.

We introduced pandas and the way to work with pandas and DataFrame objects. pandas a very powerful tool. We'll use it more in future sections, but make sure you're starting to take notice of these things because these are going to be important techniques in your Python skills for managing large amounts of data and organizing your data.