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, we avoid repeating the Rprof() results we got from ...
