One of the most attractive features of Python for people who need to analyze data is the huge ecosystem of data manipulation and analysis packages, as well as the active community of data scientists working with Python. Python is easy to use, while also offering very powerful, fast libraries, which enables even relatively novice programmers to quickly and easily process vast sets of data. At the heart of many data science packages and tools is the pandas library. Pandas provides two data container types that build on top of NumPy arrays and have good support for labels (other than simple integers). They also make working with large sets of data extremely easy.

Statistics is the systematic study of data using mathematical—specifically, probability—theory. There are two aspects to statistics. The first is to find numerical values that describe a set of data, including characteristics...