Summary

NumPy and pandas are essential tools for data wrangling. Their user-friendly interfaces and performant implementation make data handling easy. Even though they only provide a little insight into our datasets, they are valuable for wrangling, augmenting, and cleaning our datasets. Mastering these skills will improve the quality of your visualizations.

In this chapter, we learned about the basics of NumPy, pandas, and statistics. Even though the statistical concepts we covered are basic, they are necessary to enrich our visualizations with information that, in most cases, is not directly provided in our datasets. This hands-on experience will help you implement the exercises and activities in the following chapters.

In the next chapter, we will focus on the different types of visualizations and how to decide which visualization would be best for our use case. This will give you theoretical knowledge so that you know when to use a specific chart type and why. It will also lay down the fundamentals of the remaining chapters in this book, which will focus on teaching you how to use Matplotlib and seaborn to create the plots we have discussed here. After we have covered basic visualization techniques with Matplotlib and seaborn, we will dive more in-depth and explore the possibilities of interactive and animated charts, which will introduce an element of storytelling into our visualizations.