Easily achieving high benefit - cost improvements

In this section, we will show how the efficiency of R can be drastically improved without resorting to advanced techniques such as delegating to other programming languages or implementing parallelization. Those techniques will be shown in the later sections.

Using the simple data structure for the job

Many R users would agree that data frame as a data structure is a basic tool for data analysis. It provides an intuitive way to represent a typical structured dataset with rows and columns representing observations and variables, respectively, but it provides more flexibility than a matrix by allowing variables of different types (such as character and numeric variables in a single structure). Furthermore, when data frames contain only numeric variables, basic matrix operations conveniently become applicable to it without any explicit coercing required. This convenience, however, comes with a performance cost that people often don't mention.

Here...