Modern Business Analytics

Chapter 3. Introduction to R and Python

As an analytics professional, you will need to work with the popular and powerful tools. This chapter introduces you to R and Python, both open source programming languages used in business analytics. Both R and Python are highly used, and they have similar functionality. As open source programming languages, R and Python functionality is provided through the creation of packages or libraries by the open source community. (In R, these are referred to as libraries, and in Python, these are referred to as packages.) Both languages are also object-oriented, which is a programming paradigm that supports reuse, modularity, and flexibility.

R was created by statisticians in 1994, and it became the primary analytics tool during the early 2000s. R was used for statistical analysis, and it is now used by analysts and researchers globally and includes many built-in capabilities that support the analytics process. R is often accessed via RStudio, an integrated development environment (IDE), and there is an R repository. RStudio is publicly available. R is interpreted and noncompiled, which means the code runs directly from the script created.

Python is an interpreted (noncompiled) programming language that is used for analytics as well as software engineering. Python is similar to R, where a large repository of packages is available for analytics. Python has a wider community due to its portability and the general-purpose capabilities for software ...