In this chapter, you got familiar with NumPy basics for array operations and refreshed your knowledge about basic matrix operations. NumPy is an extremely important library for Python scientific stacks, with its extensive methods for array operations. You have learned how to work with multidimensional arrays and covered important topics such as indexing, slicing, reshaping, resizing, and broadcasting. The main goal of this chapter was to give you a brief idea of how NumPy works when it comes to numerical datasets, which will be helpful in your daily data analysis work.
In the next chapter, you will learn the basics of linear algebra and complete practical examples with NumPy.
