Though this is only our first look at data exploration, don't worry—this is definitely not the last time we will follow these steps for data science and exploration. From now on, every time we look at a new piece of data, we will use our steps of exploration to transform, break down, and standardize our data. The steps outlined in this chapter, while they are only guidelines, form a standard practice that any data scientist can follow in their work. The steps can also be applied to any dataset that requires analysis.
We are rapidly approaching the section of the book that deals with statistical, probabilistic, and machine learning models. Before we can truly jump into these models, we have to look at some of the basics of mathematics. In the next chapter, we will take a look at some of the math necessary to perform some of the more complicated operations in modeling, but don't worry—the math required for this process is minimal, and we will go through it step by step.