R for Data Science Cookbook

Chapter 1. Functions in R

This chapter covers the following topics:

• Creating R functions
• Matching arguments
• Understanding environments
• Working with lexical scope
• Understanding closure
• Performing lazy evaluation
• Creating infix operators
• Using the replacement function
• Handling errors in a function
• The debugging function

Introduction

R is the mainstream programming language of choice for data scientists. According to polls conducted by KDnuggets, a leading data analysis website, R ranked as the most popular language for analytics, data mining, and data science in the three most recent surveys (2012 to 2014). For many data scientists, R is more than just a programming language because the software also provides an interactive environment that can perform all ...