Summary
In this chapter, we introduced the initial concepts of how we can store and manipulate data with pandas and NumPy, and how to visualize data patterns using Seaborn. These elements are used not only to explore the data but to be able to create visual narratives that allow us to understand patterns in the data and to be able to communicate simply and practically.
In the next chapter, we will build upon this to understand how machine learning and descriptive statistics can be used to validate hypotheses, study correlations and causations, as well as to make predictive models.
