2. Python's Main Tools for Statistics
This chapter presents a practical introduction to the main libraries that most statistics practitioners use in Python. It will cover some of the most important and useful concepts, functions, and Application Programming Interfaces (APIs) of each of the key libraries. Almost all of the computational tools that will be needed for the rest of this book will be introduced in this chapter.
By the end of this chapter, you will understand the idea behind array vectorization of the NumPy library and be able to use its sampling functionalities. You'll be able to initialize pandas DataFrames to represent tabular data and manipulate their content. You'll also understand the importance of data visualization in data analysis and be able to utilize Python's two most popular visualization libraries: Matplotlib and Seaborn.