Summary
In this chapter, we ran an exploratory analysis in a live Jupyter Notebook environment. In doing so, we used visualizations such as scatter plots, histograms, and violin plots to deepen our understanding of the data. We also performed simple predictive modeling, a topic that will be the focus of the following chapters in this book.
In the next chapter, we will discuss how to approach predictive analytics and what things to consider when preparing the data for modeling. We'll use pandas to explore methods of data preprocessing, such as filling missing data, converting from categorical to numeric features, and splitting data into training and testing sets.
